Francisco Coelho · Francisco Coelho · Francisco Coelho · Francisco Coelho
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pex2024/2024-02-29_2--2023.15110.PEX.pdfInduction of Stochastic Answer Set Programs by Algebraic Means
pex2024/2024-03-01_am--2023.15110.PEX.pdf
pex2024/Application_2023.15110.PEX.pdf
pex2024/C617-7ED4-8326 (spa).pdf
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pex2024/candidatura.md
pex2024/contributions/IMG-20240229-WA0006.jpg
pex2024/contributions/IMG-20240229-WA0007.jpg
pex2024/contributions/IMG-20240229-WA0008.jpg
 # Zugzwang Meetings
  
+## 2024-03-15 - IJCAR24 Reviews
+
+### Summary
+
+- State-of-the-art:
+  - Thorough comparison with related work 
+- Motivation:
+  - Clarify the application of the approach
+  - Explore the advantages and limitations of the formalism
+- Technical details:
+  - Self-containment
+  - Detail syntax and semantics of the considered class of programs.
+  - Clarify the relation of stable models and events
+  - Recall the stable model semantics and its properties
+  - Argument for Proposition 1 [is not] convincing
+- Fixes:
+  - Provide the probabilities of the classes and of the events
+  - Clarify the role of  "testing of the prior distributions"
+  - Give a general argument [about Bayesian networks] instead of an illustration on a simple example.
+
+See [Reviews file](text/paper_01/LLNCS/reviews_IJCAR24.md).
+
+
+
+- Para ICLP24
+  - Mais técnico.
+  - Considerar scasp.
+- Para KR24
+  - Mais formal.
+- Overleaf
+  - authentication key: olp_1oPNhAUwN9ihvWzd4n92hEd9UQUbK44ul5Gg
+  - zw-kr: git clone https://git@git.overleaf.com/65f422781f1d04e2c0aefd56
+  - zw-iclp: git clone https://git@git.overleaf.com/65f422dc70a60d8ab7fde402
+
 ## 2024-01-30 - Exploratory Research Project
  
 > Apply for FCT funding.
  
  
-
 ## 2024-01-05 - Next Research Lines
  
 > After the base-setting work of "_An Algebraic Approach to Stochastic ASP_" these are the next tasks to consider. Is summary:
@@ -107,15 +140,15 @@ Scoring programs, as described in our paper, is just a step into **Inductive Log
  
 > Target conferences to publish paper "AASASP"
  
-| Conference | Abstract Deadline | Conference Date |                      Location | OBS       |
-|-----------:|:------------------|:----------------|------------------------------:|-----------|
-| IJCAR 2024 | 2024-01-29        | 2024-07-3:6     |                 Nancy, France | Picked    |
-|    ECAI'24 | 2024-04-19        | 2024-10-19:24   | Santiago de Compostela, Spain |           |
-|    KR 2024 | 2024-04-24        | 2024-11-2:8     |                Hanoi, Vietnam |           |
-|   GECCO 24 | 2024-02-05        | 2024-07-14:18   |           Melboune, Australia |           |
-|    ICLP 24 | 2024-04-15        |                 |                               | preferred |
-|   JELIA 25 |                   |                 |                               |           |
-|    ICFP 24 | 2024-03-01        | 2024-09-2:7     |                  Milan, Italy |           |
+| Conference | Abstract Deadline | Conference Date |                      Location | OBS               |
+|-----------:|:------------------|:----------------|------------------------------:|-------------------|
+| IJCAR 2024 | 2024-01-29        | 2024-07-3:6     |                 Nancy, France | ~Picked~ Rejected |
+|    ECAI'24 | 2024-04-19        | 2024-10-19:24   | Santiago de Compostela, Spain |                   |
+|    KR 2024 | 2024-04-24        | 2024-11-2:8     |                Hanoi, Vietnam |                   |
+|   GECCO 24 | 2024-02-05        | 2024-07-14:18   |           Melboune, Australia | Overdue           |
+|    ICLP 24 | 2024-04-15        |                 |                               | preferred         |
+|   JELIA 25 |                   |                 |                               |                   |
+|    ICFP 24 | 2024-03-01        | 2024-09-2:7     |                  Milan, Italy |                   |
  
 ## 2023-02-28 - Looking for Application Examples
  
@@ -173,8 +206,13 @@ What should be the **task for the scholarship student**? _Use the `Python` API o
   - Get stable models from potassco/s(casp)
   - other?
  
-
 ## 2022-12-05
  
 - Created shared folder (gdrive:zugzwang) <https://drive.google.com/drive/folders/1xs-cjxWJzn2JxqeNgh9LX5xWN50BW-Be?usp=share_link>
-- Refine project tasks, for Bachelor, M.Sc., Ph.D. students and for researchers. 
 \ No newline at end of file
+- Refine project tasks, for Bachelor, M.Sc., Ph.D. students and for researchers. 
+
+## Resources
+
+### Conferences 
+
+- [Conferences Sheet](https://docs.google.com/spreadsheets/d/1KJdA-zj3Xly-_tSE6tjbd7M9SttC9xBixXoqWZJFVfg/edit#gid=0)
 \ No newline at end of file
@@ -0,0 +1,48 @@
+- [x] Dados Gerais
+- [x] Instituições
+  - [x] Instituição proponente
+    - [x] Descrição da Instituição e respectivas competências para o desenvolvimento deste projeto (1500)
+  - [x] Instituições de colaboração (HPCC)
+- [ ] Equipa de Investigação
+  - [x] CV Narrativo do IR
+    - [x] Percurso Científico e Curricular (2000)
+    - [x] Contribuições da originalidade de ideias, ferramentas, metodologias ou conhecimento (2000)
+    - [x] Contribuições para o desenvolvimento de competências ao nível individual e/ou em equipas (3000)
+    - [x] Contribuições para a Comunidade Científica e para a Sociedade (3000)
+    - [x] Resultados ou/e atividades relevantes (2500)
+    - [x] Que relevância atribui a este financiamento para a fase atual da sua carreira e/ou do seu percurso de investigação? (3000)
+  - [ ] Membros (4)
+    - [x] Francisco
+    - [x] Bruno
+    - [x] Salvador
+    - [ ] Miguel **confirmar participação**
+  - [x] Novas contratações
+  - [x] Consultores
+  - [x] Sinopse dos CV da equipa de investigação (6000)
+    - [x] Francisco
+    - [x] Bruno
+    - [x] Salvador
+    - [x] Miguel
+- [x] Plano de Trabalho
+  - [x] Resumo PT/EN (5000 x2)
+  - [x] Estado da arte (6000)
+  - [x] Plano de investigação e métodos (10000)
+  - [x] Referências bibliográficas (10000)
+  - [x] Publicações Anteriores (5)
+    - [x] FC
+    - [x] BD
+    - [x] SPA
+    - [ ] MA **uma/duas publicações nos últimos cinco anos** 
+  - [x] Tarefas
+  - [x] Lista de milestones
+  - [x] Cronograma
+  - [x] Descrição da estrutura de gestão (3000)
+  - [x] Enquadramento da candidatura nos ODS da Agenda 2030 das Nações Unidas
+  - [x] Fundamentação do enquadramento (3000)
+  - [x] Outros projetos (5 anos)
+- [x] Indicadores
+  - [x] Divulgação (3000)
+- [x] Orçamento
+  - [x] Universidade de Évora
+  - [x] Orçamento global
+  - [x] Plano de financiamento
 \ No newline at end of file
@@ -0,0 +1,48 @@
+
+<!DOCTYPE html>
+<html>
+    <head>
+        <meta http-equiv="X-UA-Compatible" content="IE=edge" />
+        <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
+        <meta name="format-detection" content="telephone=no" />
+        <script type='text/javascript'>window.OutSystemsApp = { basePath: '/Projects/' };</script>
+        
+        
+        <meta name="viewport" content="viewport-fit=cover, width=device-width, initial-scale=1" />
+<script type="text/javascript">
+(function () {
+    function appendMetaTagAttributes(metaTag, attribute, values) {
+        var elem = document.querySelector("meta[name=" + metaTag + "]");
+
+        if (elem) {
+            var attrContent = elem.getAttribute(attribute);
+            elem.setAttribute(attribute, (attrContent ? attrContent + "," : "") + values.join(","));
+        }
+    }
+
+    if (navigator && /OutSystemsApp/i.test(navigator.userAgent)) {
+        // If this app is running on the native shell, we want to disable the zoom
+        appendMetaTagAttributes("viewport", "content", ["user-scalable=no", "minimum-scale=1.0"]);
+    }
+})();</script>
+
+        <script type="text/javascript" src="scripts/OutSystemsManifestLoader.js?3F3fZzzNKkqKoP2DsjtxFw"></script>
+<script type="text/javascript" src="scripts/OutSystems.js?RnlDcii3Xz75iIHHERIZtA"></script>
+<script type="text/javascript" src="scripts/OutSystemsReactView.js?0bmp5RZ49TZneVNXnO6ymw"></script>
+<script type="text/javascript" src="scripts/cordova.js?7KqI9_oL9hClomz1RdzTqg"></script>
+<script type="text/javascript" src="scripts/NullDebugger.js?pG_2wlzY3NYiuKZRtoLyQQ"></script>
+<script type="text/javascript" src="scripts/Projects.appDefinition.js?PrSt0mgUZuIIDvrGb3OwIg"></script>
+<script type="text/javascript" src="scripts/OutSystemsReactWidgets.js?IdWooa_erXOfwU01FQUTuA"></script>
+<link type="text/css" rel="stylesheet" href="css/_Basic.css?EqGzAe81QbZLXJyfY3oLwA"></link>
+
+        <script type="text/javascript">OSManifestLoader.indexVersionToken = "PpAVEckFK5cEx1aoSbY7vQ";
+</script>
+    </head>
+    <body>
+        <div id="reactContainer"></div>
+        <noscript><span>JavaScript is required</span></noscript>
+
+        <script type="text/javascript" src="scripts/Projects.index.js?_i_B_jY4q5y6aRAMA5bwsQ"></script>
+
+    </body>
+</html>
 \ No newline at end of file
@@ -114,6 +114,19 @@ Development Goals of the United Nations 2030 Agenda and justify how the applicat
 - **Principal Contractor**  fill in the requested funding for each budget category along with the corresponding justification.
 - **Funding Plan** Global Budget and Funding Plan tables that are automatically filled out
  
+| Rubrica                                         | 2024 | 2025 | 2026 | Total |
+|-------------------------------------------------|------|------|------|-------|
+| Recursos Humanos                                |      |      |      |       |
+| Missões                                         |      |      |      |       |
+| Instrumentos e equipamento científico e técnico |      |      |      |       |
+| Subcontratos                                    |      |      |      |       |
+| Registo de patentes                             |      |      |      |       |
+| Demonstração, Promoção e Divulgação             |      |      |      |       |
+| Adaptação de edifícios e instalações            |      |      |      |       |
+| Aquisição de bens e serviços                    |      |      |      |       |
+| Gastos gerais                                   |      |      |      |       |
+| Total                                           |      |      |      |       |
+
 ### Statement of Commitment
  
 - Mark the respective check box.
@@ -135,7 +148,6 @@ Development Goals of the United Nations 2030 Agenda and justify how the applicat
  
 ### Acceptance of Applications in myFCT
  
-
 ## Tarefas
  
 - [ ] Prepare the application carefully and timely.
@@ -189,9 +201,6 @@ MP =  0,40 (0,50 A1 + 0,50 A2) +
  
 ## Questões
  
-- O _Principal Contractor_ é a UÉvora ou o NOVALINCS?
-- 
-
 ## 2024-01-05 - Next Research Lines
  
 > After the base-setting work of "_An Algebraic Approach to Stochastic ASP_" these are the next tasks to consider. Is summary:
@@ -303,4 +312,239 @@ Scoring programs, as described in our paper, is just a step into **Inductive Log
 ## Memória Externa
  
 - [ ] Irene
-- [ ] Salvador
 \ No newline at end of file
+- [ ] Salvador
+
+
+## Contributos
+
+### Salvador Abreu
+
+#### Sinopse CV
+
+Salvador is Full Professor at the University of Évora (UE) School of Science and Technology since 2013, Senior Researcher at NOVA LINCS and President of the Scientific Council at the UE Institute for Research and Advanced Training (IIFA). He currently directs the PhD Program in Informatics at UE.
+He holds a Habilitation in Informatics from the University of Évora (2009), a PhD in Informatics from Universidade NOVA de Lisboa (1994), and a BSc in Informatics Engineering from Universidade Nova de Lisboa (1987).
+Salvador successfully supervised 9 doctoral theses and is currently directing 3. He was granted an IBM SUR award in 2013 and a JSPS Invitation Fellowship in 2015. He participates or participated as a project member or Principal Investigator in nationally and European funded projects, including OAR, AJACS, STAMPA, JEDI,
+HORUS, VAPS, BIOECOSYS, AI4EU, EUGREEN and PaCoMoCo.
+
+### Miguel Avillex
+
+#### Sinopse CV
+
+
+### Francisco Coelho
+
+
+#### Sinopse CV
+
+Francisco Coelho completed his PhD in Informatics in 2006 at Universidade de Lisboa under the supervision of Helder Coelho on Artificial Intelligence. Is previous formation is on Mathematics, where he has a Master degree in Mathematics, specialty Algebra, with a dissertation about Hilbert's tenth problem and about geometric computation, advised by Prof. Augusto Franco de Oliveira and Prof. José Félix Costa. Currently he is Assistant Professor at the Computer Science department of Universidade de Évora, where he has coordinated more than twenty courses and restructured or proposed other six, to the graduation and master degrees. He is supervising three PhD thesis and two MSc dissertations and has supervised other six completed MSc dissertations. He contributed with software and writing to papers covering a wide range of subjects but mostly about logic and statistical AI. He is integrated member of the Intelligent Systems of the research unit NOVALINCS and member of the scientific team of the High Performance Computing Chair.
+
+#### Livros
+
+2016, Introdução à Matemática - Álgebra, Análise e Otimização (LIDEL), ISBN:978-989-752-209-3
+
+2010, Teoria da Computação, Computabilidade e Complexidade (Escolar Editora), ISBN:978-972-592-281-1
+
+#### Artigos em Revista
+
+2021, Carvalho, Dias, Coelho, Neto, Nowakowski, Vinagre, On lattices from combinatorial game theory: infinite case, DOI:10.1007/s00182-020-00715-3
+
+2014, Carvalho, Santos, Dias, Coelho, Neto, Nowakowski, Vinagre, On lattices from combinatorial game theory. Modularity and a representation theorem: Finite case, DOI:10.1016/j.tcs.2014.01.025
+
+2017, Coelho e Neto, A method for regularization of evolutionary polynomial regression, DOI:10.1016/j.asoc.2017.05.047 https://doi.org/10.1016/j.asoc.2017.05.047
+
+2008, Mycka, Costa e Coelho, The Euclid abstract machine, DBLP:journals/ijuc/MyckaCC08
+
+#### Artigos em Atas de Conferências
+
+2015, Coelho e Nogueira, Probabilistic perception revision in AgentSpeak(L), DOI:10.1007/978-3-319-25524-8_44
+
+#### Software
+
+ALisP, Linguagem de programação usada para exemplificar a matéria de análise sintática na disciplina Autómatos e Linguagens de Programação e fazer a ponte para disciplinas posteriores, como Compiladores. URL:https://home.uevora.pt/~fc/alp/00-sobre_alp/alisp-py-current.zip
+
+mquestions, Biblioteca Python para escrever perguntas para o Moodle, usando YAML e Markdown. URL:https://gitlab.com/mangon/mquestions
+
+xchg, Folhas XSLT para converter ficheiros ProbModelX (pgmx) do OpenMarkov para XMLBIF. URL:https://github.com/fmgc/xchg
+
+Giraldo, Tema visual para o Beamer de acordo com a identidade visual da Universidade de Évora., URL:https://git.xdi.uevora.pt/fc/giraldo
+
+TeseUE, Classe LATEX pluridisciplinar para as teses de mestrado e dissertações de doutoramento da Universidade de Évora. URL:https://git.xdi.uevora.pt/fc/teseue
+
+jard, Ponte entre YAdrone, uma biblioteca Java para o AR.Drone 2.0 e Jason, uma biblioteca Java para o processo de deliberação AgentSpeak(L), baseado em BDI, num GUI JavaFX, URL:https://bitbucket.org/mangon/jard
+
+"Galaxity", a Java system to assess the correction of perceptions of AgentSpeak(L) agents using probabilistic methods, URL:https://bitbucket.org/mangon/galaxity
+
+jpgm, A small Java library to support simple probabilistic graphical models (pgm) computations used in Galaxity, URL:https://github.com/fmgc/jpgm.
+
+Genetic Algorithms for Polynomial Regression, Código R para encontrar a melhor regressão polinomial com algoritmos genéticos, URL:https://github.com/jpneto/GenAlgPoly
+
+CGT Toys, Ferramentas para explorar ideias em teoria combinatória de jogos, URL:https://github.com/fmgc/cgtToys
+
+Lattice-Maker, Um conjunto de ferramentas para apresentar reticulados de jogos combinatórios em LaTeX., URL:https://github.com/fmgc/Lattice-Maker
+
+
+### Bruno Dinis
+
+Bruno Dinis completed his PhD in Maths in 2013 at the University of Évora under the supervision of Imme van den Berg on Nonstandard Analysis. After his doctoral studies, he was a postdoc at the Faculdade de Ciências under the supervision of Fernando Ferreira, working on Proof Theory. Bruno Dinis is currently an Assistant Professor at the Universidade de Évora.  Co-supervised 1 master's dissertation. He has written over 20 papers on several aspects of logic, for the most part in proof interpretations and its applications (proof mining). 
+
+
+Os artigos mais relevantes (para o projecto) são:
+
+Stateful realizers for nonstandard analysis (with É. Miquey). Logical Methods in Computer Science
+Volume 19, Issue 2, 2023, pp. 7:1–7:44. doi:10.46298/LMCS-19(2:7) 2023
+
+An algebraic approach to stochastic $\mathrm{ASP}$} (with S.~Abreu and F.~Coelho). Submitted
+
+Um artigo que também considero relevante é:KO 1737/6-2
+
+Strong convergence for the alternating Halpern-Mann iteration in CAT(0) spaces (with P. Pinto).
+SIAM Journal on Optimization 33(2): 785–815, 2023. doi: 10.1137/22M1511199
+
+Quanto aos projectos a que estou associado, para além dos projectos dos centros (não sei se contam...) sou:
+ 
+Research Collaborator for Institute for Logic and Data Science -- Bucharest, Romania  -- https://ilds.ro/
+Collaborator on the DFG project ”Proof Mining in Convex Optimization and Related Areas” () 
+
+### Salvador Abreu
+
+Salvador is Full Professor at the University of Évora (UE) School of Science and Technology since 2013, Senior Researcher at NOVA LINCS and President of the Scientific Council at the UE Institute for Research and Advanced Training (IIFA). He currently directs the PhD Program in Informatics at UE.
+
+He holds a Habilitation in Informatics from the University of Évora (2009), a PhD in Informatics from Universidade NOVA de Lisboa (1994), and a BSc in Informatics Engineering from Universidade Nova de Lisboa (1987).
+
+Salvador successfully supervised 9 doctoral theses and is currently directing 3. He was granted an IBM SUR award in 2013 and a JSPS Invitation Fellowship in 2015. He participates or participated as a project member or Principal Investigator in nationally and European funded projects, including OAR, AJACS, STAMPA, JEDI, HORUS, VAPS, BIOECOSYS, AI4EU, EUGREEN and PaCoMoCo.
+
+Selected Publications
+
+[1] Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+[2] Codognet, Philippe, Daniel Diaz, and Salvador Abreu. "Quantum and Digital Annealing for the Quadratic Assignment Problem." 2022 IEEE International Conference on Quantum Software (QSW). IEEE, 2022.
+[3] Eloy, Eduardo, Vladimir Bushenkov, and Salvador Abreu. "Constraint Modeling for Forest Management." International Conference on Dynamic Control and Optimization. Cham: Springer International Publishing, 2021.
+[4] López, Jheisson, et al. "Weaving of metaheuristics with cooperative parallelism." Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, 2018, Proceedings, Part I 15. Springer International Publishing, 2018.
+[5] Codognet, P., Munera, D., Diaz, D. and Abreu, S., 2018. Parallel local search. Handbook of parallel constraint reasoning, pp.381-417
+
+
+### Universidade de Évora
+
+The University of Évora is a public University organized in 5 Schools: Arts, Sciences and Technology, Social Sciences, Health and human development, Nursing and the Institute for Advanced Studies and Research. Research and Development covers several areas through 18 Research Units, all of them submitted to international evaluation. The University of Évora has established 10 Chairs in Aerospace, Agriculture, Biodiversity, Heritage, Health, High Performance Computer, Iberian studies, UNESCO and Renewable Energies, participates in the National Roadmap of Strategic Research Infrastructures and has several research infrastructures in biodiversity, computer sciences, aerospace engineering, solar energy and heritage. The University fosters a close link with the community, enhanced through the creation of networks, the participation in the Science and Technology Park and by establishing protocols and co-promotion research projects. The main R&D areas are: Applied Mathematics; Chemistry; Culture; Education and Psychology; Healthcare; Geophysics; History; Environment and Sea; Linguistics and Literature; Materials and Surface Science; Social and Political Sciences and Science. The 300 running R&D projects are developed through national and international partnerships, under Horizon Europe, PRIMA, ERASMUS +, LIFE, Creative Europe, Digital Europe Programme, Cost Actions, EIT Health, EIT Urban Mobility, EEA Grants, INTERREG,  PT2020, Alentejo2020, COMPETE2020, PRR, FCT or private funding.
+
+### Cátedra HPC
+
+The High Performance Computing Chair (HPC) presents itself as a research and development (R&D) infrastructure dedicated to high performance computing that seeks to follow developments towards the digital transition, which enables a more efficient approach to national and European IT strategies, digital innovation for academia, companies and other public-private organizations.
+
+This new research infrastructure, in partnership with the universities of Algarve, Nova de Lisboa and Porto, has as its main objective to promote professional training between academia and industry, enhancing the development and adoption of HPC, HPDA (High Performance Data Analytics) and AI (Artificial Intelligence) by different actors in the region and at national and international levels. At the same time, it enhances the use of local advanced computing infrastructures managed by the HPC-UÉ Center, such as the OBLIVION supercomputer.
+
+### Management Structure
+
+The Administrative Services of the University of Évora are responsible for project's financial and administrative management, through its Projects Management Division (DGP). This office is organized in two areas: (i) financial contracts and administrative management and (ii) administrative support to R&D units. They are deep experienced in managing several different financial programs such as Portuguese Government Structural Funds (Portugal 2020, FCT) and Community Funds, such as Erasmus+, H2020, HORIZON EUROPE or Creative Europe.
+
+It is DGP's main task to fulfill all the necessary operations, provide administrative support and reassure the good execution of R&D Units budgets and respective Projects.  Furthermore, it is accountable for the execution of all legal and required financial reports.
+
+Each project is the responsibility of a project officer with expertise and experience in project management and finance. The project officer acts as a link between the Responsible Researcher and the rest of the financial team. Is also responsible to process all expenses fulfilling all the current national and European legislations.
+
+The project officer is also in charge of the liaison with FCT (Science and Technology National Agency), European Commission and other donors by elaborating and delivering the financial reports and respective requests for payments, including reassuring all necessary procedures to the validation of expenditures.
+
+The University of Évora owns an information system that allows the researcher to follow the project's financial implementation on a permanent basis.
+
+
+----
+
+
+### Task Denomination
+
+- Task description and expected results (4000)
+  
+  - Objectives:
+  
+  - Methodologies and approaches:
+  
+  - Expected results:
+  
+  - Preconditions from other tasks:
+  
+  - Results to other tasks:
+  
+  - Role of each partner and institution:
+    - Partner: role
+  
+  - Justification for the resources
+    - Resource: justification
+
+- Member   Person*month
+
+- StartDate Duration
+
+- Deliverables and delivery dates (2500)
+  - essential deliverable for effective project monitoring and funding; type: report, etc; ending date
+
+- Budgets (2500)
+  - item: cost estimation
+
+- Amount requested for the task 
+  - total + 25% overheads
+
+------
+
+Milestone:
+  - date
+  - denomination
+  - description (300)
+  - tasks
+
+
+------
+
+Consider a person with the CV and the PROJECT below.
+
+Explain the timeliness of that project in the context of the current stage of CV, the impact on the person future research lines and development. Career and research development potential may include scientific production, activities and dissemination, team and project leadership, establishment of national or international collaborations/networks, and the ability to enable future research and to attract funding or other resources.
+
+CV
+
+Francisco Coelho completed his PhD in Informatics in 2006 at Universidade de Lisboa under the supervision of Helder Coelho on Artificial Intelligence. Is previous formation is on Mathematics, where he has a Master degree in Mathematics, specialty Algebra, with a dissertation about Hilbert's tenth problem and about geometric computation, advised by Prof. Augusto Franco de Oliveira and Prof. José Félix Costa.
+
+Currently he is Assistant Professor at the Computer Science department of Universidade de Évora, where he has coordinated more than twenty courses and restructured or proposed other six, to the graduation and master degrees. He is supervising three PhD thesis and two MSc dissertations and has supervised other six completed MSc dissertations.
+
+He contributed with software and writing to papers covering a wide range of subjects but mostly about logic and statistical AI. He is integrated member of the Intelligent Systems of the research unit NOVALINCS and member of the scientific team of the High Performance Computing Chair.
+
+PROJECT
+
+
+This research aims to overcome the constraints of logical representations in real-world scenarios with probabilistic elements by expanding Probabilistic Logic Programming (PLP) with Stochastic Answer Set Programs (SASP). While current PLP systems like ProbLog provide some solutions, challenges persist in characterizing probability distributions for Answer Set Programs (ASP) with probabilistic facts. The proposed SASP approach introduces an algebraic method to represent uncertainty and integrates evolutionary algorithms for inducing SASP models. The research plan involves theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. Key objectives include investigating program structure and composition in SASP modeling, developing transformation rules and algorithms, and evaluating hand-coded and induced SASP models on theoretical and real-world cases.
+
+State of the Art:
+    PLP systems like ProbLog address limitations of logical representations with probability distributions.
+    However, characterizing probability distributions for Answer Set Programs extended with probabilistic facts remains challenging.
+    The proposed SASP approach extends ASP, represents uncertainty algebraically, and incorporates evolutionary algorithms for model induction.
+
+Main Goals:
+    Investigate the role of program structure in the utilization of PASP for modeling probabilistic phenomena.
+    Investigate the application of evolutionary algorithms for induction of SASP models based on additional background knowledge and evidence.
+    Evaluate hand-coded or induced SASP models, on theoretical and real-world cases.
+
+Knowledge and Skills:
+    The group possesses expertise in logic, logic programming, and distributed systems.
+    Previous work demonstrates the feasibility and representational power of SASP.
+    Collaboration with an interdisciplinary team ensures diverse perspectives.
+
+Strategy and Methodologies:
+    Theoretical analysis will explore SASP program structure effects on modeling probabilistic phenomena.
+    Algorithm development will focus on transformation rules and efficient exploration of SASP space.
+    Empirical evaluation will assess model performance on various cases.
+    Interdisciplinary collaboration fosters innovation and ensures comprehensive research.
+
+Novelty and Expected Results:
+    The novelty lies in the probabilist semantics of SASP, the resulting score based in evidence and the utilization of that score to induce SASP from background knowledge and evidence.
+    Expected results include improved understanding of SASP modeling, efficient algorithms, and validated SASP models.
+
+Overall, the proposed research addresses critical limitations in probabilistic logic programming with ASP and aims to advance the field through innovative methodologies and interdisciplinary collaboration. The comprehensive research plan, supported by existing expertise and resources, demonstrates a strong potential for significant contributions to the field.
+
+
+---
+
+Miguel Publications
+
+Breitschwerdt, D., & de Avillez, M. A. (2021). Non-equilibrium ionisation plasmas in the interstellar medium. Astrophysics and Space Science, 366, 1-21.
+
+Lioen, W., Avillez, M., & Aykanat, S., (2021), "Evaluation of Benchmark Performance", Deliverable 7.4, PRACE Sixth Implementation Phase, Final Report
+
+de Avillez, M. A., Anela, G. J., Asgekar, A., Breitschwerdt, D., & Schnitzeler, D. H. (2020). Electrons in the supernova-driven interstellar medium-Results from self-consistent time-dependent ionic and hydrodynamic evolution of the interstellar plasma. Astronomy & Astrophysics, 644, A156.
+
+Lioen, W., Avillez, M., & Codreanu, V., et al., 2019, “Evaluation of Accelerated and Non-accelerated Benchmarks”, Deliverable 7.5, PRACE Fifth Implementation Phase Project, Final Report 
 \ No newline at end of file
@@ -0,0 +1,56 @@
+# P04 - Plano de Trabalho
+
+## Resumo
+
+### Resumo em português (5000c)
+
+### Resumo em inglês (5000c)
+
+## Estado da arte e objetivos (6000c)
+
+## Plano de investigação e métodos (10000c) 
+
+## Referências bibliográficas (10000c)
+
+> Inclua publicações citadas na descrição técnica e científica da candidatura. Esta lista não está limitada a publicações dos membros da equipa. (APA, MLA, Chicago)
+
+## Publicações anteriores (5 da equipa)
+
+## Tarefas 
+
+(externo)
+
+## Calendarização e gestão do projeto
+
+### Lista de milestones
+
+### Cronograma
+
+> Produza uma descrição da calendarização do projeto em formato electrónico. Sugerimos que utilize como ponto de partida a folha de cálculo que disponibilizamos em 2 formatos: (MS Excel) e ([ODF](https://myfct.fct.pt/Projects/ProjectTimelineManagement?ApplicationId=51568#)). Converta a versão final para formato PDF e faça upload, com a designação timeline.pdf.
+
+
+## Questões éticas
+
+## Agenda 2030
+
+> Os Objetivos de Desenvolvimento Sustentável (ODS) e a Agenda 2030, adotados pela quase totalidade dos países do mundo, no contexto das Nações Unidas, definem as prioridades e aspirações do desenvolvimento sustentável global para 2030 e procuram mobilizar esforços globais à volta de um conjunto de objetivos e metas comuns. São 17 ODS, em áreas que afetam a qualidade de vida de todos os cidadãos do mundo e daqueles que ainda estão para vir. [Mais informação sobre os ODS das Nações](https://myfct.fct.pt/Projects/Agenda2030?ApplicationId=51568#).
+
+### Enquadramento da candidatura nos ODS da Agenda 2030 das Nações Unidas
+(uma linha)
+
+### Fundamentação do enquadramento (3000c)
+
+## Outros projetos
+
+> Devem ser listados as candidaturas submetidas ou projetos aprovados (liderados pelo IR) através de avaliação por pares que se tenham iniciado há menos de 5 anos (concluídos ou em curso).
+
+### JuPy
+
+#### Relação com esta candidatura
+- Foi adquirido conhecimento e experiência sobre implementação e execução de programas num sistema distribuído HPC.
+- Foram estabelecidas relações de cooperação técnica e científica entre o PI e a equipa de gestão do cluster "Oblivion | HPCUE"
+
+- Knowledge and experience was acquired about implementing and executing programs in a distributed HPC system.
+- Technical and scientific cooperation relationships were established between the PI and the management team of the "Oblivion | HPCUE" cluster.
+
+## Ficheiros anexos
@@ -0,0 +1,201 @@
+# Abstract (5000)
+
+> In this section, the summary of the proposal should be presented, in Portuguese and English, with an analysis of the state of the art, the main goals to be addressed, the knowledge and skills available in the group, the strategy and methodologies to be used, identifying the novelty and the expected results. 
+> 
+> The PI must indicate whether the abstract to be used by the FCT for public disseminating will be the same as the abstract previously filled  in. If, for confidentiality reasons, the text of the abstract for publication purposes is different, the PI should click on the button Abstract for publication different. The content of this field will always be the PI's responsibility.
+
+
+---
+
+Consider the state of the art, the research plan, and the objectives given below an present the summary, with an analysis of the state of the art, the main goals to be addressed, the knowledge and skills available in the group, the strategy and methodologies to be used, identifying the novelty and the expected results.
+
+The state of the art is:
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic when data is subject to probabilistic phenomena, which is often the case. Probabilistic Logic Programming (PLP) is one ongoing effort to address this problem by extending the syntax and semantics of logic programs in order to have them represent and operate probability distributions (see [11]). 
+
+Current systems for PLP, such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], derive a probability distribution from a program. However, for Answer Set Programs (ASP) [12] with probabilistic facts, the characterization of a probability distribution on the program's domain is not straightforward (see [1, 2, 3, 4]).
+
+In [8] we address the problem of extending probability from the total choices of an ASP program to its stable models and, from there, to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how SASP can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+This representation of arbitrary bayesian networks conferes to SASP the capability to deal with a very large collection of probability problems and tasks. However, the problem of obtaining such SASP, besides hand-coded, remains open. 
+
+In our system some unknowns are represented by numeric parameters that can be estimated later from further information, e.g., evidence. This approach, delaying the assignment of certain parameters, enables later refinement and scoring a partial program from additional evidence. 
+
+In turn, scoring of SASP (i.e., models of a probabilistic phenomenon) is a key feature required to the application of evolutionary algorithms. From here we can explore how to induce SASP from BK and evidence.
+
+The calculus of the score of an SASP with respect to evidence was already introduced and illustrated in [8]. It remains to investigate the application of this process to induction of SASP from BK and evidence. 
+
+Ideas of this paper have a partial, limited, implementation, available in a public repository, that results from the work of a BII scholarship, supported by NOVALINCS "Financiamento Plurianual da unidade de I&D UIDP/04516/2020" and co-supported by Fundação para a Ciência e a Tecnologia (FCT), Portugal.
+
+In the general Induction of Logic Programs (ILP) setting (see [11, 13]) the goal is to algorithmically obtain a (target) logic program. For that, (1) BK (e.g., obtained from experts) is provided in the form of a logic program, describing objects and (first-order) relations of a domain and (2) observations are organized as positive evidence, that should be inferred from the target program, and negative evidence, that should not be inferred from the target program. Moreover, the target program must be (logically) consistent with the BK. ILP is a form of Machine Learning (ML) that offers significant advantages over numeric based ML. 
+
+For one, ILP address the problem of Explainable Artificial Intelligence (XAI) because, unlike  the large-dimensional vector based models of numeric ML, logic programs are human-readable in the sense that their declarative nature describes what objects are in the domain, their structure, properties and relations.
+Second, ILP describes phenomena with related instances while numeric ML is limited to a single (tabulated) relation where different instances (lines) are independent given the model. 
+Third, often a target program is generated from a small set of observations, while, in general, numeric ML models require large datasets to achieve significant accuracy.
+At last, expert knowledge, expressed in the BK, can be utilized to structure the target program, i.e., to model the observations. Again, this is a feature hard to achieve with numeric ML models.
+
+Drawbacks of ILP include the computational complexity of inducing the target program and the general difficulty of logic programs to deal with data with random perturbations. While the later is being addressed by PLP in general and SASP in particular, the computational complexity of induction remains an important challenge that we propose to investigate with this project.
+
+In summary, with this project we aim to continue our exploration on how SASP represent probability distributions, how to use them to model probabilistic phenomena and how they can be induced from BK and evidence.
+
+More specifically, this project's objectives are to investigate:
+
+- The role of program structure and composition in the use of PASP to model probabilistic phenomena.
+- Program transformation rules and space exploration algorithms for SASP.
+- The performance of hand-coded and induced SASP models on selected theoretic and real world cases.
+
+The Research plan and methodologies is
+
+
+Feasibility and Originality
+
+The outlined scientific approach leverages existing developments in Probabilistic Logic Programming (PLP) and Answer Sep Programming (ASP) and extends it with the concept of Stochastic Answer Set Programs (SASP) to represent probability distributions in scenarios where traditional logical representations fall short due to probabilistic phenomena. The novelty lies in the application of algebraic methods to express uncertainty and the integration of evolutionary algorithms for inducing SASP models. Feasibility is supported by previous work demonstrating the representational power of SASP. Originality is derived from the interpretation of PLP and ASP concepts in a novel semantic, and the proposed investigation into program induction from background knowledge and evidence.
+
+Research Methodology
+
+1. **Theoretical Analysis**: Conduct a thorough analysis of the role of program structure and composition in the utilization of PASP for modeling probabilistic phenomena. This involves investigating how different program structures impact the representation and inference capabilities of SASP.
+   
+2. **Algorithm Development**: Develop program transformation rules and space exploration algorithms tailored for SASP. This includes devising methods to efficiently transform SASP representations and explore the space of possible SASP models.
+   
+3. **Empirical Evaluation**: Evaluate the performance of both hand-coded and induced SASP models on a range of theoretic and real-world cases. This involves designing experiments to assess the accuracy, scalability, and computational efficiency of SASP models in comparison to existing PLP systems.
+   
+4. **Integration of Evolutionary Algorithms**: Investigate the application of evolutionary algorithms for refining SASP models based on additional background knowledge or evidence. Develop algorithms to update SASP parameters and structure to improve model fit to observed data.
+
+Working Arrangements
+
+- Collaborative Environment: Foster collaboration between researchers with expertise in logic, logic programming, and distributed systems to ensure interdisciplinary perspectives are considered.
+  
+- Regular Meetings: Schedule regular meetings (e.g., every three/four months) to discuss progress, address challenges, and align research efforts towards the project objectives.
+  
+- Access to Resources: Ensure human and computational resources for theoretical research, algorithm development, experimentation, and data analysis.
+
+Timeline
+
+1. Task Structure and Induction of SASP (SI) (Months 1-12)
+   
+  - Theoretical research on program structure and transformation rules conducted by an interdisciplinary team of four members, including the PI.
+  - Identifications of relevant program structure and transformation rules.
+  - Regular meetings and discussions to ensure progress and collaboration within the team.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+
+2. Task Integration with existing ASP and ILP software frameworks (INT) (Months 3-15)
+  
+  - Implementation, testing, profiling and benchmarking, and documentation conducted by a post-doctoral researcher.
+  - Translation of theoretical findings into practical algorithms and software tools.
+  - Rigorous testing of implemented solutions to ensure correctness and efficiency.
+  - Profiling to identify computation intensive points for improvement.
+  - Benchmarking against existing methods to evaluate performance and identify areas for improvement.
+  - Comprehensive documentation of the developed methodologies, including user guides and technical reports.
+  - Continuous refinement based on feedback from internal testing and validation.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+3. ask Applications of SASP (APP) (Months 6-18)
+
+  - Application of developed methodologies and software tools to theoretical and real-world problems.
+  - Case studies and experiments conducted to assess the effectiveness and scalability of the proposed approaches.
+  - Analysis of results and comparison with existing state-of-the-art methods.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+Resources
+
+- Personnel
+
+    - PI: Leads and coordinates all tasks, providing guidance and oversight throughout the project duration.
+    - Interdisciplinary team (4 members, including the PI): Comprising experts in logic, logic programming, and distributed systems, responsible for theoretical research and case exploration.
+    - Post-doctoral researcher: Leads the implementation, testing, benchmarking, and documentation efforts.
+
+- Equipment and Infrastructure
+
+    - High-performance computing resources for conducting complex simulations and experiments.
+    - Software development tools and platforms for coding, testing, and version control.
+    - Access to relevant databases, datasets, and computational libraries for validation and benchmarking.
+
+- Funding
+
+    - Budget allocation for equipment procurement, travel expenses, publication fees, and other project-related costs.
+    - Grant funding to sustain the research and software tools development activities over the designated timeline.
+
+PI Commitment
+
+As the Principal Investigator (PI), I am fully committed to overseeing and ensuring the success of each phase of the research project. My responsibilities include:
+
+- Providing strategic direction and vision for the research activities.
+- Facilitating interdisciplinary collaboration among team members.
+- Securing necessary resources and funding to support the project goals.
+- Monitoring progress and addressing any challenges or setbacks that may arise.
+- Ensuring compliance with ethical guidelines and research protocols.
+- Contributing to the dissemination of research outcomes through publications, presentations, and knowledge sharing initiatives.
+- Mentoring and supporting team members to foster their professional development and growth.
+  
+Throughout the project duration, I will maintain open communication channels with all stakeholders, including team members, funding agencies, and collaborators, to ensure transparency and alignment with project objectives. My dedication to the project's success is unwavering, and I am committed to achieving impactful results that advance the field of probabilistic logic programming and inductive logic programming.
+
+Justification
+
+The proposed research methodology aligns with the project's objectives by combining theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. The utilization of existing PLP frameworks as a foundation and the integration of evolutionary algorithms introduce innovative elements to address the challenges of data with random perturbations and computational complexity in logic-based probabilistic reasoning. The allocated timelines, resources, and PI's commitment are justified by the ambitious nature of the research objectives and the potential impact of the proposed advancements in probabilistic logic programming.
+
+
+---
+
+## Abstract
+
+This research aims to overcome the constraints of logical representations in real-world scenarios with probabilistic elements by expanding Probabilistic Logic Programming (PLP) with Stochastic Answer Set Programs (SASP). While current PLP systems like ProbLog provide some solutions, challenges persist in characterizing probability distributions for Answer Set Programs (ASP) with probabilistic facts. The proposed SASP approach introduces an algebraic method to represent uncertainty and integrates evolutionary algorithms for inducing SASP models. The research plan involves theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. Key objectives include investigating program structure and composition in SASP modeling, developing transformation rules and algorithms, and evaluating hand-coded and induced SASP models on theoretical and real-world cases.
+
+State of the Art:
+    PLP systems like ProbLog address limitations of logical representations with probability distributions.
+    However, characterizing probability distributions for Answer Set Programs extended with probabilistic facts remains challenging.
+    The proposed SASP approach extends ASP, represents uncertainty algebraically, and incorporates evolutionary algorithms for model induction.
+
+Main Goals:
+    Investigate the role of program structure in the utilization of PASP for modeling probabilistic phenomena.
+    Investigate the application of evolutionary algorithms for induction of SASP models based on additional background knowledge and evidence.
+    Evaluate hand-coded or induced SASP models, on theoretical and real-world cases.
+
+Knowledge and Skills:
+    The group possesses expertise in logic, logic programming, and distributed systems.
+    Previous work demonstrates the feasibility and representational power of SASP.
+    Collaboration with an interdisciplinary team ensures diverse perspectives.
+
+Strategy and Methodologies:
+    Theoretical analysis will explore SASP program structure effects on modeling probabilistic phenomena.
+    Algorithm development will focus on transformation rules and efficient exploration of SASP space.
+    Empirical evaluation will assess model performance on various cases.
+    Interdisciplinary collaboration fosters innovation and ensures comprehensive research.
+
+Novelty and Expected Results:
+    The novelty lies in the probabilist semantics of SASP, the resulting score based in evidence and the utilization of that score to induce SASP from background knowledge and evidence.
+    Expected results include improved understanding of SASP modeling, efficient algorithms, and validated SASP models.
+
+Overall, the proposed research addresses critical limitations in probabilistic logic programming with ASP and aims to advance the field through innovative methodologies and interdisciplinary collaboration. The comprehensive research plan, supported by existing expertise and resources, demonstrates a strong potential for significant contributions to the field.
+
+## Sumário
+
+Esta pesquisa visa superar as restrições das representações lógicas em cenários do mundo real com elementos probabilísticos, expandindo a Programação Lógica Probabilística (PLP) com Programas Estocásticos de Conjunto de Respostas (SASP). Embora os sistemas PLP atuais, como o ProbLog, forneçam algumas soluções, persistem desafios na caracterização de distribuições de probabilidade para Programas de Conjunto de Respostas (ASP) com fatos probabilísticos. A abordagem SASP proposta introduz um método algébrico para representar a incerteza e integra algoritmos evolutivos para induzir modelos SASP. O plano de pesquisa envolve análise teórica, desenvolvimento de algoritmos, avaliação empírica e colaboração interdisciplinar. Os principais objetivos incluem investigar a estrutura e composição do programa na modelação SASP, desenvolver regras e algoritmos de transformação e avaliar modelos SASP codificados manualmente e induzidos em casos teóricos e do mundo real.
+
+Estado da arte
+    Sistemas PLP como o ProbLog abordam limitações de representações lógicas com distribuições de probabilidade.
+    No entanto, caracterizar distribuições de probabilidade para ASP estendidos com fatos probabilísticos permanece um desafio.
+    A abordagem SASP proposta estende ASP, representa a incerteza algebricamente e incorpora algoritmos evolutivos para indução de modelos.
+
+Objetivos principais
+    Investigar o papel da estrutura dos programa na utilização de SASP na modelação de fenómenos probabilísticos.
+    Investigar a aplicação de algoritmos evolutivos para indução de modelos SASP com base em conhecimento e evidências adicionais.
+    Avaliar modelos SASP codificados manualmente ou induzidos, em casos teóricos e do mundo real.
+
+Conhecimento e competências
+    O grupo tem experiência em lógica, programação lógica e sistemas distribuídos.
+    Trabalhos anteriores demonstram a viabilidade e a capacidade representativa dos SASP.
+    A colaboração numa equipe interdisciplinar garante diversas perspetivas.
+
+Estratégia e Metodologias
+    A análise teórica explorará os efeitos da estrutura dos programas SASP na modelação de fenómenos probabilísticos.
+    O desenvolvimento de algoritmos será focado on uso de SASP para a modelação de fenómenos probabilísticos e indução indução de modelos SASP.
+    A avaliação empírica irá apurar o desempenho dos modelos em vários casos.
+    A colaboração interdisciplinar promove a inovação e garante pesquisas abrangentes.
+
+Novidade e resultados esperados
+    A novidade está na semântica probabilística do SASP, na pontuação resultante baseada em evidências e na utilização dessa pontuação para induzir SASP a partir de conhecimento anterior e evidência.
+    Os resultados esperados incluem melhor compreensão da modelação SASP, algoritmos eficientes e modelos SASP validados.
+
+No geral, a pesquisa proposta aborda limitações críticas na programação lógica probabilística com ASP e visa avançar através de metodologias inovadoras e colaboração interdisciplinar. O plano de investigação abrangente, apoiado pelos conhecimentos e recursos existentes, demonstra um forte potencial para contribuições significativas para esse problema.
 \ No newline at end of file
@@ -0,0 +1,26 @@
+using Dates
+
+function budget(items, overhead=0.25)
+    partial = sum(items)
+    partial_overhead = overhead * partial
+    total = partial + partial_overhead
+    return (partial, partial_overhead, total)
+end
+
+function get_budget()
+    items = [700, 500, 576, 2660, 12*1686]
+    (partial, overhead, total) = budget(items)
+    println("Partial : $(partial)\nOverhead: $(overhead)\nTotal   : $total")
+end
+
+function project_month(n, startdate=Date(2024,09,01))
+    months = Dates.Month(n)
+    return startdate + months
+end
+
+function get_month(month=8)
+    cm = project_month(month)
+    println("M$(month) -> $(cm)")
+end
+
+get_budget()
 \ No newline at end of file
@@ -0,0 +1,196 @@
+
+
+<!-- Since 2022, Integrated Member of the "Intelligent Systems" group of the research unit NOVALINCS.
+
+Twelve articles published in international journals or conference proceedings (>= Core B and Q2).
+
+Since 2011, author and co-author of nine computer programs and systems, available in public repositories, of academic or pedagogical content, available in public repositories. 
+
+Since  1997, university professor, having taught more than twenty undergraduate or master's courses.
+
+Since 2022, Supervisor of three doctoral students (in progress) and seven master's students (in progress and completed).
+
+-->
+
+# Narrative CV
+
+
+  - Contributions to the generation of new ideas, tools, methodologies, or knowledge
+  - Contributions to the development of individuals and/or research teams
+  - Contributions to the research community and the broader society
+  - Selected outputs and/or activities
+  - Why would this grant be timely for me, at this point in my career path and/or in my research?
+
+## Career profile (2000)
+
+> a summary of the PI's education (specifying the year the PhD was completed), key qualifications, and employment history. If applicable, any period of leave from research, such as parental leaves, long-term absence due to illness, period of work in industry, secondments, volunteering, or other non-research activities may be specified. Explain how these interruption(s) or the unconventional path and/or gap(s) has/have impacted your activity.
+
+1993, Degree in Mathematics, Faculdade de Ciências, Universidade de Lisboa.
+1997, MSc in Mathematics (Algebra), Faculdade de Ciências, Universidade de Lisboa. On Hilbert's tenth problem and a computational model based on geometric constructions with ruler and compass.
+1997, Teaching Assistant, Mathematics Department, Universidade de Évora.
+2006, PhD in Informatics (Computer Science), Universidade de Lisboa. On deliberation by autonomous agents.
+2006, Assistant Professor, Mathematics Department, Universidade de Évora.
+2006, Assistant Professor, Computer Science Department, Universidade de Évora.
+2008 -- 2021, Teaching and research and teaching activity on ideas about computing and geometry, started in the master's dissertation; the integration of logic and statistical AI; learning polynomial models using genetic algorithms, with several publications, e.g., articles and books; 
+2021 -- present, Researcher at the chair "High Performance Computing" at Universidade de Évora; Integrated member of the NOVALINCS center; Preparation and lecturing of courses on the Julia language, aimed at the digital humanities and social sciences, under the HPC Chair and the european projects EuroCC and EuroCC2, funded by  the European Commission - EuroHPC Joint Undertaking: PI of the project CPCA/A0/427668/2021, FCT, Portugal, a small FCT founded project exploring the use of "high-level" languages (Julia, Python) in distributed computing and HPC systems; Work on the extension of ASP with probabilistic annotations, and respective induction by a set of data and background knowledge; Supervisor of a BII scholarship 
+
+## Contributions to Science and Society
+
+### Contributions to the generation of new ideas, tools, methodologies or knowledge (2000)
+
+> description of how the PI has contributed to the generation of new ideas, tools,
+methodologies, or knowledge, and
+>
+> the relevance and impact of your contributions.
+>
+> publications, key data sets, software, intellectual property (patents, licenses, trademarks, copyrights, novel assays, and reagents), conference presentations and proceedings, research, and policy publications, or other scientific, technological, cultural or artistic achievements; 
+> 
+> What + how + where
+
+2021, Mentor of i-Days: Student competition to tackle health challenges, organized by EIT-Health and StartUB!C (Universidad de Barcelona), that took place in PACT, Évora. i-Days promote health innovation among university students through dozens of one-day and two-day programmes held in academic institutions around Europe.
+
+2021, Co-author of "Lattice-Maker", a set of tools to present lattices of combinatorial games in LaTeX, used on the PhD thesis "Lattices related to Conway's construction", where I was member of the juri, and two papers where I'm co-author: DOI:10.1016/j.tcs.2014.01.025 and DOI:10.1007/s00182-020-00715-3
+
+2017, Co-author of "Genetic Algorithms for Polynomial Regression", R code to find the best polynomial regression using genetic algorithms, used in the journal paper DOI:10.1016/j.asoc.2017.05.047.
+
+2015, Author of "Galaxity", a Java system to assess the correction of perceptions of AgentSpeak(L) agents using probabilistic methods, and used in the conference paper DOI:10.1007/978-3-319-25524-8_44.
+
+2014, Author of "TeseUE", a LaTeX class to MSc dissertations and PhD thesis in Universidade de Évora, is currently used by many students.
+
+### Contributions to the development of individuals and/or research teams (3000)
+
+> expertise provided by the PI which was relevant to the development of individuals and/or teams
+> 
+> project participation, leadership or management, collaborative contributions, and team support. Contributions to the development of individuals and/or research teams
+> 
+> Teaching activities, workshops, summer schools,  the supervision of students, mentoring or other contributions to the success of a team or advancement of colleagues.
+> role: PI, team member, other; ongoing or past funded projects;
+
+
+2024, Mentor of the mini-project "Automatic Differentiation", aimed at MSc and PhD students, at the Birla Institute of Technology and Science, Pilani, India, within the Asian and European Schools in Mathematics. Travel was supported by a CIMPA scholarship.
+
+2024, Lecturer of the course "An Introduction to Julia for Scholars", aimed at MSc and PhD students and researchers, at the Birla Institute of Technology and Science, Pilani, India, within the Asian and European Schools in Mathematics. Travel was supported by a CIMPA scholarship.
+
+2023, 2024, Coordinator and lecturer of the online course "Programming in Julia for Digital Humanities", aimed to digital humanities and social sciences researchers, part of the training and dissemination activities of the HPC Centre and the HPC Chair.
+
+2023, 2024, Mentor of one BII Scholarship within the scope of the multi-annual financing of the R&D unit with reference UIDP/04516/2020, financed by national funds through the FCT/MCTES.
+
+2022 -- present, Supervisor of three ongoing PhD thesis on computer science.
+
+2016 -- present, Course director and lecturer of "Introdução ao LaTeX"  (Introduction to LaTeX), directed at students and researchers, at Universidade de Évora.
+
+2016, Co-author of the book "Introdução à Matemática - Álgebra, Análise e Otimização"(LIDEL), ISBN:978-989-752-209-3, addressing core mathematical subjects (algebra, calculus and optimization) for social sciences university courses. Used in the course "Matemática Aplicada à Economia e Gestão", Universidade de Évora.
+
+2010 -- present, Supervisor of six completed and three ongoing MSc dissertations about topics such as e-learning, virtual reality, serious games or game design.
+
+2010 -- present, Member of the juri in 13 academic examinations, including three as examiner.
+
+2010, co-author of the book "Teoria da Computação, Computabilidade e Complexidade", ISBN:978-972-592-281-1, where computation is explained starting with simple machines, addressing the computation limits such as the Halting Problem, polynomial equivalence and complexity. A draft version of this book was used in the course "Teoria da Computabilidade e Complexidade", Universidade de Évora.
+
+2006 -- present, Assistant professor at Universidade de Évora. Within this role I coordinated more than 26 courses, including mathematics and computer science, for graduation or MSc grades.
+
+### Contributions to the research community and the broader society (3000)
+
+> activities the PI has participated in to progress the research community and engage with the broader society.
+> 
+> editing, reviewing, refereeing, evaluation of funding applications; and organization of events that have benefited the research community, or improved research culture
+
+
+2024, An introduction course to the Julia language, for students on technical courses and researchers.
+2024, A mini-project/introduction course to automatic derivation with Python, for students of technical courses.
+2023, 2024, An introduction course to the Julia language, for researchers in the areas of digital humanities and social sciences.
+2024, 2023, 2010, Visited higher education institutions in India, the Czech Republic and Timor-Lorosa'e to disseminate knowledge and to establish or reinforce cooperation between Universidade de Évora and local HEI.
+2023, Invited Talk, "Fronteiras da Inteligência Artificial", Festival da Ciência'23,  Universidade de Évora, aimed at societal engagement with science.
+2022 -- present, Reviewer for the "Applied Soft Computing" journal (Q1).
+2021 -- present, Participation in the "High Performance Computing Chair" of Universidade de Évora, as member of the scientific team, technical-scientific board, coordinator of the "Programming in Digital Humanities" task and member of five work packages.
+2016 -- present, Course director and lecturer of "Introdução ao LaTeX"  (Introduction to LaTeX), directed at students and researchers, at Universidade de Évora.
+2016, 2010, Co-author of two pedagogical books, about Mathematics and Computer Science, aimed at higher education students, contributions to the dissemination of knowledge.
+2011 -- present, Member of several organizing and scientific committees of international scientific events. In the most recent, the international conference "Programming and Data Infrastructure in Digital Humanities", I was member of both the scientific and organizing committee.
+1997 -- present, Fifteen communications at scientific dissemination events, either at international conferences or invited to scientific lectures.
+
+### Selected outputs and/or activities (2500)
+
+> provide additional and detailed information on a maximum of five scientific outputs and/or activities that **best describes the PI's research career and experience**. For each one, the PI should indicate his/her role and how it has impacted the advancement of knowledge in the respective scientific area. Any type of contribution from the three previous sections can be also included. Whenever the outputs have a DOI, please include it.
+
+Activity "Combinatorial Games Theory" and results
+
+    Contributed to the development of "Lattice-Maker", a set of tools to present lattices of combinatorial games in LaTeX, available in the public repository <https://github.com/fmgc/Lattice-Maker>.
+    Lattice-Maker was used by Cátia Dias on her PhD thesis "Lattices related to Conway's construction" where I was member of the juri, and in two international, indexed, jornal papers:
+        2021, Carvalho, Dias, Coelho, Neto, Nowakowski, Vinagre, "On lattices from combinatorial game theory: infinite case", DOI:10.1007/s00182-020-00715-3
+        2014, Carvalho, Santos, Dias, Coelho, Neto, Nowakowski, Vinagre, "On lattices from combinatorial game theory. Modularity and a representation theorem: Finite case", DOI:10.1016/j.tcs.2014.01.025
+
+Activity "Polynomial Regression" and results
+
+    Contributed to "Genetic Algorithms for Polynomial Regression", R code to find the best polynomial regression using genetic algorithms, available in the public repository <https://github.com/jpneto/GenAlgPoly>.
+    This program was used in the international, indexed, journal paper
+    2017, Coelho e Neto, "A method for regularization of evolutionary polynomial regression", DOI:10.1016/j.asoc.2017.05.047
+    This is my most cited work, some of which two in 2023, six years after publishing.
+
+Activity "Perception Correction" and results
+
+    Implemented "Galaxity", a Java system to assess the correction of perceptions of AgentSpeak(L) agents using probabilistic methods, and "jpgm", a small Java library to support simple probabilistic graphical models (pgm) computations used in Galaxity. These are available in the public repositories <https://bitbucket.org/mangon/galaxity> and <https://github.com/fmgc/jpgm>.
+    "Galaxity" (and "jpgm") where used in the conference paper 
+        2015, Coelho e Nogueira, "Probabilistic perception revision in AgentSpeak(L)", DOI:10.1007/978-3-319-25524-8_44
+
+Activity "Stochastic Answer Set Programs" and results
+
+Started in 2023 and is currently my main research activity, a continuation of "Perception Correction" towards the combination of statistical ans logic AI. At this moment the outcomes of this activity are
+    
+    BII scholarship, supported by "Financiamento Plurianual da unidade de I&D UIDP/04516/2020", co-supported by FCT, Portugal.
+    Draft programs, available in a public repository.
+    A paper, "An Algebraic Approach to Stochastic ASP", in co-authorship, recently submitted to a international conference.
+
+### Why would this grant be timely for me at this point in my career path and/or in my research? (3000)
+
+> explain the timeliness of this project in the context of the current stage of his/her career, and/or the impact on his/her future research lines and development. Career and research development potential may include scientific production, activities and dissemination, team and project leadership, establishment of national or international collaborations/networks, and the ability to enable future research and to attract funding or other resources.
+
+Given my background and this project research area there are several aspects to consider regarding the timeliness and potential impact of this project on my future research lines and development:
+
+Alignment with Current Expertise. My expertise in logic and statistical AI, as evidenced by contributions to papers covering these subjects, aligns well with the objectives of the proposed project, which aims to overcome constraints in logical representations with probabilistic elements. My previous work in these areas provides a solid foundation for tackling the challenges outlined in the project.
+
+Interdisciplinary Collaboration. The project emphasizes interdisciplinary collaboration, crucial in addressing complex research problems. My involvement in this interdisciplinary effort showcases my ability to collaborate across domains, enhancing my network and potentially leading to future collaborations and research opportunities.
+
+Contribution to the Field. The proposed research addresses critical limitations in probabilistic logic programming, an area of increasing importance in AI and machine learning. By expanding Answer Set Programming with Stochastic Answer Set Programs, this project seeks to advance the field through innovative methodologies, such as assigning probability to general events and integration of evolutionary algorithms for model induction. My involvement can improve my profile within the academic community and position me as a competent expert in this specialized area.
+
+Career Development Potential. Engaging in this project not only enhances my research credentials but also provides opportunities for career development. As a researcher, my involvement in cutting-edge research projects can strengthen my position within the academic community, attract funding for future research endeavors, and potentially lead to leadership roles within research teams or initiatives.
+
+Establishment of Collaborations. This project emphasis on interdisciplinary collaboration and the integration of diverse perspectives ensures that I will have the opportunity to establish national and potential international collaborations/networks. These can lead to joint publications, participation in conferences, and access to resources that further enrich my research carrear.
+
+Potential for Future Funding. Successful completion of the project and the generation of impactful results can significantly enhance my ability to attract funding for future research projects. My involvement in this research can strengthen my competitiveness in securing research grants.
+
+This project aligns well with my expertise and offers significant potential for advancing my career and research development. Through interdisciplinary collaboration, contributions to the field, and the establishment of collaborations, I can leverage this project to make substantial strides in my research trajectory and position myself as a competent authority in the field of probabilistic logic programming.
+
+
+<!-- 
+2006, PhD thesis about deliberation.
+
+Deliberation, selecting an action from perceptions and internal state, embodies the key challenges of AI, from computer vision to planning, learning, complexity or the frame problem. Each can be stated as a statistical problem (eg POMDP) or as a logical one (eg "plans" as formal expressions processed by symbolic rules).
+
+Each has strengths and weaknesses. Statistical models require large amounts of data to train while inductive logic programs often result from background knowledge and small sets of examples but the former are robust to noise while the latter are fragile.
+
+By then my research main interest become how to combine the strengths of statistical and logic AI.
+
+2015, author of Galaxity, a system to play with correction of perceptions of logic agents using probabilistic methods; Described in DOI:10.1007/978-3-319-25524-8_44, a initial study on combining logic and statistical AI.
+
+BDI agents often win planning competitions where, unlike real scenarios, perception is perfect. The Galaxity system introduces noise in the agent's perception and uses a HMM to estimate the probability of the real state. This is then tested in simulations, outperforming other agents also subject to probabilistic phenomena.
+
+Despite the positive result, this is a shallow approach with no substantial theoretical base to support further work.
+
+By then I have learned about probabilistic logic programming, the Sato semantics and Markov logic.
+
+Also, my participation in the NOVALINCS research unit opened new opportunities.
+
+Since 2023, mentor of a BII Scholarship about Stochastic Answer Set Programs (SASP), financed by national funds through FCT/MCTES: UIDP/04516/2020; NOVALINCS (UIDB/04516/2020).
+
+Answer Set Programming (ASP) is a pure declarative logic language with excellent tool support and theoretical foundations (Gelfond and Lifschitz stable models). Semantics for probabilistic versions of ASP have been proposed but the problem is still very much open.
+
+My, Bruno Dinis and Salvador Abreu approach is described in "An Algebraic Approach to Stochastic ASP", recently submitted to an international conference.
+
+We address the problem of extending probability from total choices to stable models, and from there to general events. Possible applications include assigning a score to a logic program with respect to the empiric distribution of a dataset, which can be used by evolutionary algorithms searching optimal models of that dataset. From there we have induction of stochastic ASP.
+
+This paper is the root to the research proposed with this project:
+
+Investigate the structure and composition of SASP and transformation rules to support program space search by evolutionary algorithms.
+Implement a library to support SASP evaluation using existing ASP systems.
+Explore how distributed HPC systems can be used to scale-up and speed-up the evaluation of SASP.
+Investigate the application of SASP to theoretical and real-world problems. -->
 \ No newline at end of file
@@ -0,0 +1,147 @@
+# Research plan and methods
+
+> In this section, the PI should describe the proposed research plan and the methodologies to be used, focusing on the following questions:
+> - To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
+> - To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
+> - To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
+> 
+> Funded projects will now have access to advanced computer resources and research data repositories provided by FCT without the need for further scientific evaluation. This includes computing time in FCT's two new supercomputers, Deucalion and MareNostrum 5. To this end, FCT kindly requests that applicants answer two simple yes/no additional questions:
+> - Identify whether the work plan requires advanced computer resources to be provided by FCT.
+> - Identify whether the work plan requires space in a research data repository to be provided by the FCT.
+
+---
+
+Consider the following state of the art and describe a research plan and the methodologies to be used, focusing on the following questions:
+
+- To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
+
+- To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
+
+- To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
+
+The state of the art is:
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Probabilistic Logic Programming (PLP) is one ongoing effort to address this problem by extending the syntax and semantics of logic programs in order to have them represent and operate probability distributions. 
+
+Current systems for PLP, such as ProbLog, P-log, LP^MLN, or cplint, derive a probability distribution from a program. However, for Answer Set Programs (ASP)  with probabilistic facts, the characterization of a probability distribution on the program's domain is not straightforward .
+
+In a previous work we address the problem of extending probability from the total choices of an ASP program to its stable models and, from there, to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how SASP can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+This representation of arbitrary bayesian networks conferes to SASP the capability to deal with a very large collection of probability problems and tasks. However, the problem of obtaining such SASP, besides hand-coded, remains open. 
+
+In our system some unknowns are represented by numeric parameters that can be estimated later from further information, e.g., evidence. This approach, delaying the assignment of certain parameters, enables later refinement and scoring a partial program from additional evidence. 
+
+In turn, scoring of SASP (i.e., models of a probabilistic phenomenon) is a key feature required to the application of evolutionary algorithms. From here we can explore how to induce SASP from BK and evidence.
+
+The calculus of the score of an SASP with respect to evidence was already introduced and illustrated in . It remains to investigate the application of this process to induction of SASP from BK and evidence. 
+
+Ideas of this paper have a partial, limited, implementation, available in a public repository.
+
+In the general Induction of Logic Programs (ILP) setting the goal is to algorithmically obtain a (target) logic program. For that, (1) BK (e.g., obtained from experts) is provided in the form of a logic program, describing objects and (first-order) relations of a domain and (2) observations are organized as positive evidence, that should be inferred from the target program, and negative evidence, that should not be inferred from the target program. Moreover, the target program must be (logically) consistent with the BK. ILP is a form of Machine Learning (ML) that offers significant advantages over numeric based ML. 
+
+For one, ILP address the problem of Explainable Artificial Intelligence (XAI) because, unlike  the large-dimensional vector based models of numeric ML, logic programs are human-readable in the sense that their declarative nature describes what objects are in the domain, their structure, properties and relations.
+Second, ILP describes phenomena with related instances while numeric ML is limited to a single (tabulated) relation where different instances (lines) are independent given the model. 
+Third, often a target program is generated from a small set of observations, while, in general, numeric ML models require large datasets to achieve significant accuracy.
+At last, expert knowledge, expressed in the BK, can be utilized to structure the target program, i.e., to model the observations. Again, this is a feature hard to achieve with numeric ML models.
+
+Drawbacks of ILP include the computational complexity of inducing the target program and the general difficulty of logic programs to deal with data with random perturbations. While the later is being addressed by PLP in general and SASP in particular, the computational complexity of induction remains an important challenge that we propose to investigate with this project.
+
+In summary, with this project we aim to continue our exploration on how SASP represent probability distributions, how to use them to model probabilistic phenomena and how they can be induced from BK and evidence.
+
+More specifically, this project's objectives are to investigate:
+
+- The role of program structure and composition in the use of PASP to model probabilistic phenomena.
+- Program transformation rules and space exploration algorithms for SASP.
+- The performance of hand-coded and induced SASP models on selected theoretic and real world cases.
+
+---
+
+### Research Plan and Methodologies
+
+Feasibility and Originality
+
+The outlined scientific approach leverages existing developments in Probabilistic Logic Programming (PLP) and Answer Set Programming (ASP) and extends it with the concept of Stochastic Answer Set Programs (SASP) to represent probability distributions in scenarios where traditional logical representations fall short due to probabilistic phenomena. The novelty lies in the application of algebraic methods to express uncertainty and the integration of evolutionary algorithms for inducing SASP models. Feasibility is supported by previous work demonstrating the representational power of SASP. Originality is derived from the interpretation of PLP and ASP concepts in a novel semantic, and the proposed investigation into program induction from background knowledge and evidence.
+
+Research Methodology
+
+1. **Theoretical Analysis**: Conduct a thorough analysis of the role of program structure and composition in the utilization of PASP for modeling probabilistic phenomena. This involves investigating how different program structures impact the representation and inference capabilities of SASP.
+   
+2. **Algorithm Development**: Develop program transformation rules and space exploration algorithms tailored for SASP. This includes devising methods to efficiently transform and combine SASP representations and explore the space of possible SASP models.
+   
+3. **Empirical Evaluation**: Evaluate the performance of both hand-coded and induced SASP models on a range of theoretic and real-world cases. This involves designing experiments to assess the accuracy, scalability, and computational efficiency of SASP models in comparison to existing PLP systems.
+   
+4. **Integration of Evolutionary Algorithms**: Investigate the application of evolutionary algorithms for induction of SASP models based on additional background knowledge and evidence. Develop algorithms to update SASP parameters and structure to improve model fit to observed data.
+
+Working Arrangements
+
+- Collaborative Environment: Foster collaboration between researchers with expertise in logic, logic programming, and distributed systems to ensure interdisciplinary perspectives are considered.
+  
+- Regular Meetings: Schedule regular meetings (e.g., every three/four months) to discuss progress, address challenges, and align research efforts towards the project objectives.
+  
+- Access to Resources: Ensure human and computational resources for theoretical research, algorithm development, experimentation, and data analysis.
+
+Timeline
+
+1. Task Structure and Induction of SASP (SI) (Months 1-12)
+   
+  - Theoretical research on program structure and transformation rules conducted by an interdisciplinary team of four members, including the PI.
+  - Identifications of relevant program structure and transformation rules.
+  - Regular meetings and discussions to ensure progress and collaboration within the team.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+
+2. Task Integration with existing ASP and ILP software frameworks (INT) (Months 3-15)
+  
+  - Implementation, testing, profiling and benchmarking, and documentation conducted by a post-doctoral researcher.
+  - Translation of theoretical findings into practical algorithms and software tools.
+  - Rigorous testing of implemented solutions to ensure correctness and efficiency.
+  - Profiling to identify computation intensive points for improvement.
+  - Benchmarking against existing methods to evaluate performance and identify areas for improvement.
+  - Comprehensive documentation of the developed methodologies, including user guides and technical reports.
+  - Continuous refinement based on feedback from internal testing and validation.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+3. ask Applications of SASP (APP) (Months 6-18)
+
+  - Application of developed methodologies and software tools to theoretical and real-world problems.
+  - Case studies and experiments conducted to assess the effectiveness and scalability of the proposed approaches.
+  - Analysis of results and comparison with existing state-of-the-art methods.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+Resources
+
+- Personnel
+
+    - PI: Leads and coordinates all tasks, providing guidance and oversight throughout the project duration.
+    - Interdisciplinary team (4 members, including the PI): Comprising experts in logic, logic programming, and distributed systems, responsible for theoretical research and case exploration.
+    - Post-doctoral researcher: Leads the implementation, testing, benchmarking, and documentation efforts.
+
+- Equipment and Infrastructure
+
+    - High-performance computing resources for conducting complex simulations and experiments.
+    - Software development tools and platforms for coding, testing, and version control.
+    - Access to relevant databases, datasets, and computational libraries for validation and benchmarking.
+
+- Funding
+
+    - Budget allocation for equipment procurement, travel expenses, publication fees, and other project-related costs.
+    - Grant funding to sustain the research and software tools development activities over the designated timeline.
+
+PI Commitment
+
+As the Principal Investigator (PI), I am fully committed to overseeing and ensuring the success of each phase of the research project. My responsibilities include:
+
+- Providing strategic direction and vision for the research activities.
+- Facilitating interdisciplinary collaboration among team members.
+- Securing necessary resources and funding to support the project goals.
+- Monitoring progress and addressing any challenges or setbacks that may arise.
+- Ensuring compliance with ethical guidelines and research protocols.
+- Contributing to the dissemination of research outcomes through publications, presentations, and knowledge sharing initiatives.
+- Mentoring and supporting team members to foster their professional development and growth.
+  
+Throughout the project duration, I will maintain open communication channels with all stakeholders, including team members, funding agencies, and collaborators, to ensure transparency and alignment with project objectives. My dedication to the project's success is unwavering, and I am committed to achieving impactful results that advance the field of probabilistic logic programming and inductive logic programming.
+
+Justification
+
+The proposed research methodology aligns with the project's objectives by combining theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. The utilization of existing PLP frameworks as a foundation and the integration of evolutionary algorithms introduce innovative elements to address the challenges of data with random perturbations and computational complexity in logic-based probabilistic reasoning. The allocated timelines, resources, and PI's commitment are justified by the ambitious nature of the research objectives and the potential impact of the proposed advancements in probabilistic logic programming.
 \ No newline at end of file
@@ -0,0 +1,613 @@
+# Work Plan [DRAFT]
+
+## Abstract [DRAFT]
+
+> In this section, the summary of the proposal should be presented, in Portuguese and English, with an analysis of the state of the art, the main goals to be addressed, the knowledge and skills available in the group, the strategy and methodologies to be used, identifying the novelty and the expected results. 
+> 
+> The PI must indicate whether the abstract to be used by the FCT for public disseminating will be the same as the abstract previously filled  in. If, for confidentiality reasons, the text of the abstract for publication purposes is different, the PI should click on the button Abstract for publication different. The content of this field will always be the PI's responsibility.
+
+### PT (5000)  [DRAFT]
+
+[DRAFT]
+
+Esta pesquisa visa superar as restrições das representações lógicas em cenários do mundo real com elementos probabilísticos, expandindo a Programação Lógica Probabilística (PLP) com Programas Estocásticos de Conjunto de Respostas (SASP). Embora os sistemas PLP atuais, como o ProbLog, forneçam algumas soluções, persistem desafios na caracterização de distribuições de probabilidade para Programas de Conjunto de Respostas (ASP) com fatos probabilísticos. A abordagem SASP proposta introduz um método algébrico para representar a incerteza e integra algoritmos evolutivos para induzir modelos SASP. O plano de pesquisa envolve análise teórica, desenvolvimento de algoritmos, avaliação empírica e colaboração interdisciplinar. Os principais objetivos incluem investigar a estrutura e composição do programa na modelação SASP, desenvolver regras e algoritmos de transformação e avaliar modelos SASP codificados manualmente e induzidos em casos teóricos e do mundo real.
+
+Estado da arte
+    Sistemas PLP como o ProbLog abordam limitações de representações lógicas com distribuições de probabilidade.
+    No entanto, caracterizar distribuições de probabilidade para ASP estendidos com fatos probabilísticos permanece um desafio.
+    A abordagem SASP proposta estende ASP, representa a incerteza algebricamente e incorpora algoritmos evolutivos para indução de modelos.
+
+Objetivos principais
+    Investigar o papel da estrutura dos programa na utilização de SASP na modelação de fenómenos probabilísticos.
+    Investigar a aplicação de algoritmos evolutivos para indução de modelos SASP com base em conhecimento e evidências adicionais.
+    Avaliar modelos SASP codificados manualmente ou induzidos, em casos teóricos e do mundo real.
+
+Conhecimento e competências
+    O grupo tem experiência em lógica, programação lógica e sistemas distribuídos.
+    Trabalhos anteriores demonstram a viabilidade e a capacidade representativa dos SASP.
+    A colaboração numa equipa interdisciplinar garante diversas perspetivas.
+
+Estratégia e Metodologias
+    A análise teórica explorará os efeitos da estrutura dos programas SASP na modelação de fenómenos probabilísticos.
+    O desenvolvimento de algoritmos será focado on uso de SASP para a modelação de fenómenos probabilísticos e indução indução de modelos SASP.
+    A avaliação empírica irá apurar o desempenho dos modelos em vários casos.
+    A colaboração interdisciplinar promove a inovação e garante pesquisas abrangentes.
+
+Novidade e resultados esperados
+    A novidade está na semântica probabilística do SASP, na pontuação resultante baseada em evidências e na utilização dessa pontuação para induzir SASP a partir de conhecimento anterior e evidência.
+    Os resultados esperados incluem melhor compreensão da modelação SASP, algoritmos eficientes e modelos SASP validados.
+
+No geral, a pesquisa proposta aborda limitações críticas na programação lógica probabilística com ASP e visa avançar através de metodologias inovadoras e colaboração interdisciplinar. O plano de investigação abrangente, apoiado pelos conhecimentos e recursos existentes, demonstra um forte potencial para contribuições significativas para esse problema.
+
+### EN (5000) [DRAFT]
+
+[DRAFT]
+
+This research aims to overcome the constraints of logical representations in real-world scenarios with probabilistic elements by expanding Probabilistic Logic Programming (PLP) with Stochastic Answer Set Programs (SASP). While current PLP systems like ProbLog provide some solutions, challenges persist in characterizing probability distributions for Answer Set Programs (ASP) with probabilistic facts. The proposed SASP approach introduces an algebraic method to represent uncertainty and integrates evolutionary algorithms for inducing SASP models. The research plan involves theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. Key objectives include investigating program structure and composition in SASP modeling, developing transformation rules and algorithms, and evaluating hand-coded and induced SASP models on theoretical and real-world cases.
+
+State of the Art:
+    PLP systems like ProbLog address limitations of logical representations with probability distributions.
+    However, characterizing probability distributions for Answer Set Programs extended with probabilistic facts remains challenging.
+    The proposed SASP approach extends ASP, represents uncertainty algebraically, and incorporates evolutionary algorithms for model induction.
+
+Main Goals:
+    Investigate the role of program structure in the utilization of PASP for modeling probabilistic phenomena.
+    Investigate the application of evolutionary algorithms for induction of SASP models based on additional background knowledge and evidence.
+    Evaluate hand-coded or induced SASP models, on theoretical and real-world cases.
+
+Knowledge and Skills:
+    The group possesses expertise in logic, logic programming, and distributed systems.
+    Previous work demonstrates the feasibility and representational power of SASP.
+    Collaboration with an interdisciplinary team ensures diverse perspectives.
+
+Strategy and Methodologies:
+    Theoretical analysis will explore SASP program structure effects on modeling probabilistic phenomena.
+    Algorithm development will focus on transformation rules and efficient exploration of SASP space.
+    Empirical evaluation will assess model performance on various cases.
+    Interdisciplinary collaboration fosters innovation and ensures comprehensive research.
+
+Novelty and Expected Results:
+    The novelty lies in the probabilist semantics of SASP, the resulting score based in evidence and the utilization of that score to induce SASP from background knowledge and evidence.
+    Expected results include improved understanding of SASP modeling, efficient algorithms, and validated SASP models.
+
+Overall, the proposed research addresses critical limitations in probabilistic logic programming with ASP and aims to advance the field through innovative methodologies and interdisciplinary collaboration. The comprehensive research plan, supported by existing expertise and resources, demonstrates a strong potential for significant contributions to the field.
+
+## State of the art and Objectives (6000)  [DRAFT]
+
+> In this section, the PI must provide an overview of his/her research field, present the state of the art of the research area in connection with the ground-breaking nature and potential impact of the proposed research project. References to the PI's previous work should be included. The PI should focus on the following questions:
+> - To what extent does the proposed research **address important challenges**?
+> - To what extent are the **objectives ambitious and beyond the state of the art** (e.g. novel concepts and approaches or development between or across disciplines)?
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic when dealing with probabilistic phenomena, which is often the case. Probabilistic Logic Programming (PLP) is one ongoing effort to address this problem by extending the syntax and semantics of logic programs in order to have them represent and operate probability distributions (see [11]).
+
+Answer Set Programming (ASP) [12] is a logic programming paradigm based on the stable model semantics of normal programs that can be implemented using the latest advances in SAT solving technology. Unlike ProLog, ASP is a truly declarative language that supports language constructs such as disjunction in the head of a clause, choice rules, and both hard and weak constraints.
+
+Current systems for PLP, such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], derive a unique probability distribution from the probabilistic facts of a Prolog-like program. However, if instead of Prolog we consider ASP with probabilistic facts, the characterization of a probability distribution on the program's domain is no more uniquely determined (see [1, 2, 3, 4]).
+
+In our recent, yet unpublished, work [8] we address the problem of extending probability from the probabilistic facts of an (extended) ASP program to its stable models and, from there, to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and non-uniqueness is expressed by algebraic variables related by polynomial expressions. In that work we show how SASP can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+This representation of arbitrary bayesian networks conferes to SASP the capability to deal with a very large collection of probability problems and tasks. However, the problem of obtaining such SASP, besides hand-coded, remains open. 
+
+In our system some unknowns are represented by algebraic variables that can be estimated later from further information, e.g., evidence. This approach, delaying the assignment of these variables, enables later refinement and assigning a score to a partial program from additional evidence, measuring the error between the program's probability distribution and the empirical distribution from the evidence. 
+
+In turn, scoring of SASP (i.e., models of probabilistic phenomena) is a feature that can be utilized with the application of evolutionary algorithms. From here we can explore how to induce SASP from BK and evidence, using the SASP score as a fitness function for the selection step in evolutionary algorithms.
+
+The calculus of the score of an SASP with respect to evidence was already introduced and illustrated in [8]. It remains to investigate the application of this process to induction of SASP from BK and evidence. 
+
+Ideas of this paper have a partial, limited, implementation, available in a public repository, that results from the work of a BII scholarship, supported by NOVALINCS "Financiamento Plurianual da unidade de I&D UIDP/04516/2020" and co-supported by Fundação para a Ciência e a Tecnologia (FCT), Portugal.
+
+In the general Induction of Logic Programs (ILP) setting (see [11, 13]), the goal is to algorithmically obtain a (target) logic program consistent with BK and evidence. For that, (1) BK (e.g., obtained from experts) is provided in the form of a logic program, that describes objects and (first-order) relations of a domain and (2) observations are organized as positive evidence, that should be inferred from the target program, and negative evidence, that should not be inferred from the target program. Moreover, the target program must be (logically) consistent with the BK. ILP is a form of Machine Learning (ML) that offers significant advantages over numeric based ML. 
+
+For one, ILP address the problem of Explainable Artificial Intelligence (XAI) because, unlike  the large-dimensional vector based models of numeric ML, logic programs are human-readable in the sense that their declarative nature describes what objects are in the domain, their structure, properties and relations.
+Second, ILP describes phenomena with related instances while numeric ML is limited to a single (tabulated) relation where different instances (lines) are independent given the model. 
+Third, often a target program is generated from a small set of observations, while, in general, numeric ML models require large datasets to achieve significant accuracy.
+At last, expert knowledge, expressed in the BK, can be utilized to structure the target program, i.e., to model the observations. Again, this is a feature hard to achieve with numeric ML models.
+
+Drawbacks of ILP include the computational complexity of inducing the target program and the general difficulty of logic programs to deal with data from probabilistic phenomena. While the later is being addressed by PLP in general and SASP in particular, the computational complexity of induction remains an important challenge that we propose to address with this project objectives.
+
+We aim to continue our exploration, started in the work described in [8] and a BII scholarship, on how SASP represent probability distributions, how to use them to model probabilistic phenomena and how they can be induced from BK and evidence.
+
+More specifically, this project's objectives are to investigate:
+
+- The role of program structure and composition in the use of PASP to model probabilistic phenomena.
+- Program transformation rules and space exploration algorithms for SASP.
+- The performance of hand-coded and induced SASP models on selected theoretic and real world cases.
+
+<!-- 
+In summary, this project's objectives are:
+
+- Induce SASP from BK and evidence, a form of machine learning that addresses the problem of Explainable Artificial Intelligence by producing structured, knowledge based, models.
+- 
+This is an ambitious objective that we plan to follow with this project by:
+
+- Investigate the effects of program structure and composition in the use of PASP to model , (2) program transformation rules in task "Structure and Induction of SASP (SI)" and in tasks (3) "Integration with existing ASP and ILP software frameworks (INT)" and (4) "High Performance Computing for Induction and Use of SASP (HPC)". These tasks should provide software tools to use and induce SASP, the former task for general use and the former utilizing distributed HPC to speed-up and scale-up applications of SASP.  
+
+Current systems ([3, 5, 6, 7]) adhere to a semantic of probabilistic logic programs different from ours. Therefore, it is necessary to provide a set of software tools to use and induce SASP.
+
+Application state of the art and Objectives
+-->
+
+
+## Research plan and methods (10000) [DRAFT]
+
+> In this section, the PI should describe the proposed research plan and the methodologies to be used, focusing on the following questions:
+> - To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
+> - To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
+> - To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
+> 
+> Funded projects will now have access to advanced computer resources and research data repositories provided by FCT without the need for further scientific evaluation. This includes computing time in FCT's two new supercomputers, Deucalion and MareNostrum 5. To this end, FCT kindly requests that applicants answer two simple yes/no additional questions:
+> - Identify whether the work plan requires advanced computer resources to be provided by FCT.
+> - Identify whether the work plan requires space in a research data repository to be provided by the FCT.
+
+[DRAFT]
+
+Feasibility and Originality
+
+The outlined scientific approach leverages existing developments in Probabilistic Logic Programming (PLP) and Answer Set Programming (ASP) and extends it with the concept of Stochastic Answer Set Programs (SASP) to represent probability distributions in scenarios where traditional logical representations fall short due to probabilistic phenomena. The novelty lies in the application of algebraic methods to express uncertainty of and the integration of evolutionary algorithms for inducing SASP models. Feasibility is supported by previous work demonstrating the representational power of SASP. Originality is derived from the interpretation of PLP and ASP concepts, such as facts, of stable models and general event, with a new distribution semantic featuring unknown quantities that can be refined with evidence, and the proposed investigation into program induction from background knowledge and evidence.
+
+Research Methodology
+
+1. **Theoretical Analysis**: Conduct a thorough analysis of the role of program structure and composition in the utilization of PASP for modeling probabilistic phenomena. This involves investigating how different program structures impact the representation and inference capabilities of SASP.
+   
+2. **Algorithm Development**: Develop program transformation rules and space exploration algorithms tailored for SASP. This includes devising methods to efficiently transform SASP representations and explore the space of possible SASP models.
+   
+3. **Empirical Evaluation**: Evaluate the performance of both hand-coded and induced SASP models on a range of theoretical and real-world cases. This involves designing experiments to assess the accuracy, scalability, and computational efficiency of SASP models in comparison to existing PLP systems.
+   
+4. **Integration of Evolutionary Algorithms**: Investigate the application of evolutionary algorithms for refining SASP models based on additional background knowledge or evidence. Develop algorithms to update SASP parameters and structure to improve model fit to observed data.
+
+Working Arrangements
+
+- Collaborative Environment: Foster collaboration between researchers with expertise in logic, logic programming, and distributed systems to ensure interdisciplinary perspectives are considered.
+  
+- Regular Meetings: Schedule regular meetings (e.g., every three months) to discuss progress, address challenges, and align research efforts towards the project objectives.
+  
+- Access to Resources: Ensure human and computational resources for theoretical research, algorithm development, experimentation, and data analysis.
+
+Timeline
+
+1. Task Structure and Induction of SASP (SI) (Months 1-12)
+   
+  - Theoretical research on program structure and transformation rules conducted by an interdisciplinary team of four members, including the PI.
+  - Identifications of relevant program structure and transformation rules.
+  - Regular meetings and discussions to ensure progress and collaboration within the team.
+  - Publication of research findings in two peer-reviewed international journals or presentations at international conferences.
+
+2. Task Integration with existing ASP and ILP software frameworks (INT) (Months 3-15)
+  
+  - Implementation, testing, profiling and benchmarking, and documentation conducted by a post-doctoral researcher.
+  - Translation of theoretical findings into practical algorithms and software tools.
+  - Rigorous testing of implemented solutions to ensure correctness and efficiency.
+  - Profiling to identify computation intensive points for improvement.
+  - Benchmarking against existing methods to evaluate performance and identify areas for improvement.
+  - Comprehensive documentation of the developed methodologies, including user guides and technical reports.
+  - Continuous refinement based on feedback from internal testing and validation.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+3. ask Applications of SASP (APP) (Months 6-18)
+
+  - Application of developed methodologies and software tools to theoretical and real-world problems.
+  - Case studies and experiments conducted to assess the effectiveness and scalability of the proposed approaches.
+  - Analysis of results and comparison with existing state-of-the-art methods.
+  - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
+  - Dissemination of outcomes through seminars, and open-source repositories.
+
+Resources
+
+- Personnel
+
+    - PI: Leads and coordinates all tasks, providing guidance and oversight throughout the project duration.
+    - Interdisciplinary team (4 members, including the PI): Comprising experts in logic, logic programming, and distributed systems, responsible for theoretical research and case exploration.
+    - Post-doctoral researcher: Leads the implementation, testing, benchmarking, and documentation efforts.
+
+- Equipment and Infrastructure
+
+    - High-performance computing resources for conducting complex simulations and experiments. For example, High Performance Computing Chair's OBLIVION super-computer.
+    - Software development tools and platforms for coding, testing, and version control.
+    - Access to relevant databases, datasets, and computational libraries for validation and benchmarking.
+
+- Funding
+
+    - Budget allocation for equipment procurement, travel expenses, publication fees, and other project-related costs.
+    - Grant funding to sustain the research and software tools development activities over the designated timeline.
+
+PI Commitment
+
+As the Principal Investigator (PI), I am fully committed to overseeing and ensuring the success of each phase of the research project. My responsibilities include:
+
+- Providing strategic direction and vision for the research activities.
+- Facilitating interdisciplinary collaboration among team members.
+- Securing necessary resources and funding to support the project goals.
+- Monitoring progress and addressing any challenges or setbacks that may arise.
+- Ensuring compliance with ethical guidelines and research protocols.
+- Contributing to the dissemination of research outcomes through publications, presentations, and knowledge sharing initiatives.
+- Mentoring and supporting team members to foster their professional development and growth.
+  
+Throughout the project duration, I will maintain open communication channels with all  team members, funding agencies, and collaborators, to ensure transparency and alignment with project objectives. My dedication to the project's success is unwavering, and I am committed to achieving impactful results that advance the field of probabilistic logic programming and inductive logic programming.
+
+Justification
+
+The proposed research methodology aligns with the project's objectives by combining theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. The utilization of existing PLP frameworks as a foundation and the integration of evolutionary algorithms introduce innovative elements to address the challenges of data with random perturbations and computational complexity in logic-based probabilistic reasoning. The allocated timelines, resources, and PI's commitment are justified by the ambitious nature of the research objectives and the potential impact of the proposed advancements in probabilistic logic programming.
+
+
+## Bibliographic References (10000) [DRAFT]
+
+> This section is intended to include the references cited in the state of art and in the research plan and methods, with a cross-referencing methodology chosen by the PI, namely: APA, MLA or Chicago.
+> 
+> The following elements are considered for each reference: title; authors' names in the order in which they appear in the publication; name of the book or journal; editorial data, where applicable; volume number; page numbers; year of publication. If the publications are available electronically, you can add their URL, although this is not mandatory.
+> 
+> Bibliographical references are not limited to the PI and team members' publications.
+
+1. Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: Semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239.
+2. Verreet, V., Derkinderen, V., Dos Martires, P. Z., & De Raedt, L. (2022, June). Inference and learning with model uncertainty in probabilistic logic programs. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 9, pp. 10060-10069).
+3. Baral, C., Gelfond, M., & Rushton, N. (2009). Probabilistic reasoning with answer sets. Theory and Practice of Logic Programming, 9(1), 57-144.
+4. Pajunen, J., & Janhunen, T. (2021). Solution enumeration by optimality in answer set programming. Theory and Practice of Logic Programming, 21(6), 750-767.
+5. De Raedt, L., Kimmig, A., & Toivonen, H. (2007). ProbLog: A probabilistic Prolog and its application in link discovery. In IJCAI 2007, Proceedings of the 20th international joint conference on artificial intelligence (pp. 2462-2467). IJCAI-INT JOINT CONF ARTIF INTELL.
+6. Lee, J., & Wang, Y. (2016, March). Weighted rules under the stable model semantics. In Fifteenth international conference on the principles of knowledge representation and reasoning.
+7. Alberti, M., Bellodi, E., Cota, G., Riguzzi, F., & Zese, R. (2017). cplint on SWISH: Probabilistic logical inference with a web browser. Intelligenza Artificiale, 11(1), 47-64.
+8. Coelho, F., Dinis, B., & Abreu, S. (2024).  An Algebraic Approach to Stochastic ASP. Submitted.
+9.  Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+10. López, J., Múnera, D., Diaz, D., & Abreu, S. (2018). Weaving of metaheuristics with cooperative parallelism. In Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part I 15 (pp. 436-448). Springer International Publishing.
+11. Riguzzi, F. (2022). Foundations of probabilistic logic programming: Languages, semantics, inference and learning. River Publishers.
+12. Lifschitz, V. (2002). Answer set programming and plan generation. Artificial Intelligence, 138(1-2), 39-54.
+13. Russell, S. J., & Norvig, P. (2010). Artificial intelligence a modern approach. London.
+
+## Past publications [DRAFT]
+
+[1] Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+[2] Codognet, Philippe, Daniel Diaz, and Salvador Abreu. "Quantum and Digital Annealing for the Quadratic Assignment Problem." 2022 IEEE International Conference on Quantum Software (QSW). IEEE, 2022.
+[3] Eloy, Eduardo, Vladimir Bushenkov, and Salvador Abreu. "Constraint Modeling for Forest Management." International Conference on Dynamic Control and Optimization. Cham: Springer International Publishing, 2021.
+[4] López, Jheisson, et al. "Weaving of metaheuristics with cooperative parallelism." Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, 2018, Proceedings, Part I 15. Springer International Publishing, 2018.
+[5] Codognet, P., Munera, D., Diaz, D. and Abreu, S., 2018. Parallel local search. Handbook of parallel constraint reasoning, pp.381-417
+
+## Tasks [DRAFT]
+
+### Structure and Induction of SASP (SI) [DRAFT]
+
+- Task description and expected results (4000)
+  
+    Objectives
+
+    Understand the role of Stochastic Answer Set Programs (SASP) structure and composition elements (e.g., stratified or recursive  programs, functional symbols) on the stable models, event classes, respective probability and SASP scoring with respect to evidence (i.e., a dataset).
+    
+    Understand what are the best choices for program transformation and combination rules for induction of SASP from Background Knowledge (BK) and evidence using evolutionary program space exploration algorithms (e.g., genetic algorithms).
+  
+    Methodologies and approaches
+
+    List structure elements (e.g., stratified programs, recursive rules, functional symbols) and explore the respective effects on the stable models and event classes.
+    
+    Modify the definition of event classes and study the effect on event probability and score function in modeling probabilistic processes
+    
+    Define SASP transformation and combination rules to study and characterize the resulting properties of evolutionary program space exploration algorithms for the induction of SASP from BK and evidence. 
+  
+    Expected results
+
+    Assessment on the effects of SASP structures and composition elements on stable models, event classes, respective probability and SASP scoring with respect to evidence for the use of SASP in modeling probabilistic processes.
+    
+    Assessment of SASP transformation and combination rules and the resulting properties of evolutionary program space exploration algorithms for the induction of SASP from BK and evidence.
+  
+    Preconditions from other tasks: None. This is an initial task, a continuation of previous research.
+  
+    Results to other tasks
+
+    Expected result of this task gives important insights into:
+        To tasks INT and APP
+        The use of SASP in modeling probabilistic processes, because it studies the elements utilized in the computation of the event classes and respective probabilities.
+        The induction of SASP from BK and evidence, because it studies program transformation and combination rules utilized in evolutionary program space exploration algorithms.
+  
+    Role of each partner and institution:
+    
+    Universidade de Évora: Principal contractor;
+
+    Francisco Coelho's expertise in Informatics and AI, coupled with his extensive teaching and research experience, qualifies him to investigate SASP structures and their role in probabilistic modeling. His contributions to logic and statistical AI ensure insightful analysis of SASP transformation rules. The expected results will deepen understanding of SASP's applicability in modeling probabilistic processes.
+
+    With expertise in proof theory and logic, Bruno Dinis is well-equipped to analyze SASP structures and transformation rules. His research background ensures insightful assessment of SASP's role in logic modeling, contributing to advancements in algorithmic induction methodologies.
+
+    Salvador Abreu's vast experience in informatics, leadership in research, and project management make him invaluable for analyzing SASP structures. His insights will enhance understanding of SASP's role in probabilistic modeling and optimize induction methodologies.
+  
+  - Justification for the resources:
+    For deliverable "SI Paper 1": A member should present the results of this task in an international, peer-review, conference or journal.
+    For deliverable "SI Paper 2": A member should present the results of this task in an international, peer-review, conference or journal.
+
+- Member   Person*month
+    Francisco Coelho    2,00
+    Bruno Dinis         2,00
+    Salvador Abreu      1,00
+
+- StartDate Duration
+    2024-09-01  12
+
+- Deliverables and delivery dates (2500)
+  Paper accepted in international conference or journal, by 2025-03-01
+  Paper accepted in international conference or journal, by 2025-09-01
+
+- Budgets (2500)
+  Registration in international conference (x2)....1400.00€
+  Travel to international conference (x2)..........1000.00€
+  Per diem international conference (x3x2).........1152.00€
+
+- Amount requested for the task 
+  4440.00€
+
+### Integration with existing ASP and ILP software frameworks (INT) [DRAFT]
+
+- Task description and expected results (4000)
+  
+    Objectives
+
+    Support the application of SASP for modeling probabilistic processes and induce SASP from Background Knowledge (BK) and evidence.
+  
+    Methodologies and approaches
+
+    Implementation (i.e., writing code according to the software design specifications), testing (i.e., verification that the implemented software functions correctly and meets the requirements outlined in the design phase), profiling (i.e., analyzing the performance of the software system to identify bottlenecks, memory leaks, and other performance issues), benchmarking (i.e., compare the performance of the software system against standard benchmarks or competitors' products) and documenting (i.e., providing comprehensive information about the software system, including its purpose, features, architecture, installation instructions, and usage guidelines): 
+        SASP intermediate representation and a parser.
+        Integration with existing, state of the art, Answer Set Program (ASP) tools such as Potassco and cplint for the computation of the stable models.
+        Instrumental functions such as: event belongs to class, class probability, event probability.
+        Support for SASP combination and transformation.
+        Integration with existing, state of the art, evolutionary explorations tools (e.g. genetic algorithms).
+        Command-line programs to support basic usage such as: list classes, query the probability of an event or class, induce SASP.
+  
+    Expected results
+
+    A basic set of tools, including a library and command-line programs, to use Stochastic Answer Set Programs (SASP) for modeling probabilistic processes and induce SASP from Background Knowledge (BK) and evidence.
+  
+    Preconditions from other tasks
+
+    From task SI, 
+        Insights on the relation of SASP structure and composition elements and the computation of classes, and element and class probability.
+        Insights on the effects of SASP transformation and combination rules on evolutionary program space exploration algorithms.
+  
+    Results to other tasks
+    
+    The software tools required by task APP to use and/or induce SASP on large problems.  
+  
+    Role of each partner and institution
+
+    Universidade de Évora: Principal contractor.
+
+    Francisco Coelho, PhD in Informatics, specializes in AI and mathematics. As Assistant Professor at Universidade de Évora, he aims to support SASP application by developing a robust toolset, ensuring effective probabilistic modeling through integration, instrumentation, and evolutionary exploration.
+
+    The post-doc student will implement, test, profile, benchmark, and document software for SASP application. Integration with existing ASP tools, instrumental functions, and evolutionary exploration will ensure effective probabilistic modeling. The expected outcome is a comprehensive SASP toolset for modeling and inference.
+  
+    Justification for the resources
+    
+    The implementation volume and complexity requires a full-time post-doc student working over a year, using a suitable laptop.
+    The student should present the results of this task in an international conference or journal.
+    
+
+- Member   Person*month
+  
+  Francisco Coelho   2,00
+  Post-doc Student  12,00
+
+- StartDate Duration
+
+    2024-12-01  12
+
+- Deliverables and delivery dates (2500)
+    
+    A report on progress, documenting the implementation, testing, benchmarking and documentation of the tools, by 2025-06-01.
+    Paper accepted in international conference or journal, by 2025-12-01.
+
+- Budgets (2500)
+
+  Registration in international conference.......700.00€
+  Travel to international conference.............500.00€
+  Per diem international conference (x3).........576.00€
+  Laptop (i7, 32GB ram, 1TB SSD, 15")...........2660.00€
+  Post-doc scholarship (BPD) (12 x 1686,00€)...20232.00€
+
+- Amount requested for the task 
+  30835.00€
+
+### Applications of SASP (APP) [DRAFT]
+
+- Task description and expected results (4000)    
+    Objectives
+
+    Use Stochastic Answer Set Programs (SASP) for modeling probabilistic processes and induce SASP from Background Knowledge (BK) and evidence in the context of theoretic scenarios (toy problems) described in the relevant literature (e.g., Stochastic Plan Generation, Logic/Statistic Puzzles) as well as to a selected real-world cases, including modelling resource allocation in distributed, high performance computing systems.
+
+    Methodologies and approaches
+
+    Compile a set of theoretic and real-world problems, including resource allocation in distributed, high performance computing systems.
+    Gather information in the form of background knowledge (e.g., from experts) and data (positive and negative examples) on selected problems.
+    Evaluate the performance of hand-coded and induced SASP models on that set of problems.
+    Compare with state-of-the-art results.
+
+    Expected results
+
+    Assessment of the performance of hard-coded and induced SASPs on selected theoretical and real-world problems, with focus on resource allocation in distributed, high performance computing systems.
+    Hard-coded or induced models of the addressed cases.
+    A list of advantages and problems in the application of SASP.
+  
+    Preconditions from other tasks
+
+    From task SI:
+      Insights on the relation of SASP structure and composition elements and the computation of classes, and element and class probability.
+      Insights on the effects of SASP transformation and combination rules on evolutionary program space exploration algorithms.
+    From task INT:
+        Libraries, programs, and respective documentation. 
+  
+    Results to other tasks
+      None. This is a final task.
+  
+    Role of each partner and institution
+
+    Universidade de Évora: Principal contractor.
+
+    High Performance Computing Chair: Research unit.
+
+    Francisco Coelho's vast experience in informatics, mathematics, and AI makes him instrumental in SASP modeling. His supervision ensures rigorous evaluation, leading to insights into SASP's applicability and challenges.
+
+    Salvador Abreu's expertise in informatics and extensive project involvement make him pivotal for SASP modeling. His leadership will ensure thorough problem compilation, data gathering, and performance evaluation, yielding insights into SASP's effectiveness.
+
+    Miguel Avillez’s profound expertise in astrophysics and high-performance computing is vital for SASP modeling. His leadership ensures comprehensive problem evaluation and performance assessment, yielding insights into SASP’s applicability and limitations.
+  
+    Justification for the resources
+
+    A member should present the results of this task in an international, peer-review, conference or journal.
+    
+
+- Member   Person*month
+  
+Francisco Coelho    2,00
+Salvador Abreu      1.00
+Miguel Avillez      1.00
+
+- StartDate Duration
+
+2025-03-01  12
+
+- Deliverables and delivery dates (2500)
+    
+A report on progress, documenting the performance of the hand-coded and induced PASP models on the selected problems, by 2025-09-01.
+A paper accepted in an international conference or journal, by 2026-03-01.
+
+- Budgets (2500)
+
+Registration in international conference......1400.00€
+Travel to international conference............1000.00€
+Per diem international conference (x3)........1152.00€
+
+- Amount requested for the task 
+  4440€
+
+## Project timeline and management [DRAFT]
+
+### Milestones list (<= 6) [DONE]
+
+SI Paper 1:
+  - 2025-03-01
+  - SI Paper 1
+  - A paper accepted in an international conference or journal, describing the effects of structures and composition elements on SASP on stable models, event classes, and respective probability.
+  - SI
+
+SI Paper 2:
+  - 2025-09-01
+  - SI Paper 2
+  - A paper accepted in an international conference or journal, describing program transformation rules and space exploration algorithms for SASP.
+  - SI
+
+INT Report:
+  - 2025-06-01
+  - INT Report
+  - A report on progress, documenting the implementation, testing, benchmarking and documentation of the tools.
+  - INT
+
+INT Paper:
+  - 2025-12-01
+  - INT Paper
+  - A paper accepted in an international conference or journal, describing the performance of the implemented tools on hand-coded and induced SASP.
+  - INT
+
+APP Report:
+  - 2025-09-01
+  - APP Report
+  - A report on progress, documenting the performance of the hand-coded and induced PASP models on selected problems.
+  - APP
+
+APP Paper:
+  - 2026-03-01
+  - APP Paper
+  - A paper accepted in an international conference or journal, documenting the performance of the hand-coded and induced PASP models on selected problems.
+  - APP
+
+### Timeline [DONE]
+
+(Use the spreadsheet)
+
+### Management (3000) [DRAFT]
+
+> in this section, the PI should include a description of the project management structure to be adopted, in particular the coordination between participants, the meetings planned and the reporting structure. The proposed structure will depend on the size of the project and, in particular, the existence of participants from different research units.
+
+[DRAFT]
+
+**Project Management Structure:**
+
+1. **Coordination Between Participants:**
+   - **Principal Investigator (PI):**
+     - Leads the overall project and ensures alignment with objectives.
+     - Facilitates communication between participants from different research units.
+     - Provides guidance and support to team members.
+
+   - **Researchers:**
+     - Collaborate closely with the PI to execute project tasks.
+     - Coordinate with each other to ensure seamless progress on individual and collaborative activities.
+     - Contribute expertise from their respective research units to enhance project outcomes.
+
+   - **Postdoctoral Student:**
+     - Works closely with the PI and researchers to implement project tasks.
+     - Collaborates with other team members to integrate research findings into software tools and algorithms.
+
+2. **Meetings Planned:**
+   - **Quarterly Team MeetingsQuarterly Team Meetings:**
+     - Frequency: Once every three months.
+     - Purpose: Discuss progress, challenges, and next steps for the quarter; Provide a comprehensive overview of progress across all project tasks.
+     - Agenda: Review individual tasks, share updates, address any issues or roadblocks; Review achievements, challenges, and goals for the upcoming month.
+   
+   - **Semiannual Review Meetings:**
+     - Frequency: Once every six months.
+     - Purpose: Conduct a detailed review of project milestones and objectives.
+     - Agenda: Evaluate progress, identify any necessary adjustments to the research plan, discuss potential collaborations or partnerships.
+
+3. **Reporting Structure:**
+   - **Progress Reports:**
+     - Format: Written reports submitted every three months by each team member.
+     - Content: Summarize achievements, challenges, and goals for the upcoming month.
+     - Submission: Due one week prior to the Quarterly Team Meetings.
+   
+   - **Semiannual Review Reports:**
+     - Format: Comprehensive reports submitted by the PI summarizing progress and outcomes over the past six months.
+     - Content: Review achievements, challenges, adjustments to the research plan, and any recommendations for the future.
+     - Submission: Due one week prior to the Semiannual Review Meetings.
+
+5. **Project Management Tools:**
+   - Maintain shared documentation and repositories for research materials, code, and datasets to ensure accessibility and transparency among team members.
+
+Financial and Administrative Management
+
+The Administrative Services of the University of Évora are responsible for project's financial and administrative management, through its Projects Management Division (DGP). This office is organized in two areas: (i) financial contracts and administrative management and (ii) administrative support to R&D units. They are deep experienced in managing several different financial programs such as Portuguese Government Structural Funds (Portugal 2020, FCT) and Community Funds, such as Erasmus+, H2020, HORIZON EUROPE or Creative Europe.
+
+It is DGP's main task to fulfill all the necessary operations, provide administrative support and reassure the good execution of R&D Units budgets and respective Projects. Furthermore, it is accountable for the execution of all legal and required financial reports.
+
+Each project is the responsibility of a project officer with expertise and experience in project management and finance. The project officer acts as a link between the Responsible Researcher and the rest of the financial team. Is also responsible to process all expenses fulfilling all the current national and European legislations.
+
+The project officer is also in charge of the liaison with FCT (Science and Technology National Agency), European Commission and other donors by elaborating and delivering the financial reports and respective requests for payments, including reassuring all necessary procedures to the validation of expenditures.
+
+The University of Évora owns an information system that allows the researcher to follow the project's financial implementation on a permanent basis.
+
+## Ethical issues [DONE]
+
+## 2030 Agenda (3000) [DONE]
+
+> The Sustainable Development Goals (SDGs) and the 2030 Agenda, adopted by almost all countries in the world, in the context of the United Nations, define the priorities and aspirations of global sustainable development for 2030 and seek to mobilize global efforts around a set of common goals and objectives.
+> 
+> There are 17 SDGs, in areas that affect the quality of life of all citizens of the world and those who are yet to come.
+> 
+> In this section the PI should identify one, or up to a maximum of three, of the 17 Sustainable Development Goals of the United Nations 2030 Agenda and justify how the application fits into the selected SDGs.
+
+
+SDG Goal 9: Industry, Innovation and Infrastructures
+
+Framework justification (3000)
+
+Application of this project include the optimization in the use of existing infrastructure, therefore in accordance to Target 9.b: Support domestic technology development, research and innovation in developing countries, including by ensuring a conducive policy environment for, inter alia, industrial diversification and value addition to commodities. Indicator 9.b.1: Proportion of medium and high-tech industry value added in total value added.
+
+## Other projects [DONE]
+
+- JuPy
+  - Project Reference: CPCA/A0/427668/2021
+  - PI: Francisco Coelho
+  - Project Status: completed
+  - Project Title: JuPy | High Level Languages on HPC
+  - Principal contractor: High Performance Computing Chair
+  - Funding Entity: Fundação para a Ciência e a Tecnologia - FCT, I.P.
+  - Total funding: 185,00€
+  - Start date: 2022-01-21
+  - Duration (months): 3
+  - Main objectives:
+    - Knowledge and experience acquired about implementing and executing programs in a distributed HPC system.
+    - Technical and scientific cooperation relationships established between the PI and the management team of the "Oblivion | HPCUE" cluster.
+
+## Attachments [DONE]
+
@@ -0,0 +1,143 @@
+# Work Plan
+
+## Abstract
+
+> In this section, the summary of the proposal should be presented, in Portuguese and English, with an analysis of the state of the art, the main goals to be addressed, the knowledge and skills available in the group, the strategy and methodologies to be used, identifying the novelty and the expected results. 
+> 
+> The PI must indicate whether the abstract to be used by the FCT for public disseminating will be the same as the abstract previously filled  in. If, for confidentiality reasons, the text of the abstract for publication purposes is different, the PI should click on the button Abstract for publication different. The content of this field will always be the PI's responsibility.
+
+### PT (5000)
+
+### EN (5000)
+
+Analysis of the state of the art
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Here we aim to explore how Answer Set Programs (ASP) with probabilistic facts can lead to characterizations of probability functions on the program's domain, which is not straightforward in the context of ASP (see [1, 2, 3, 4]). 
+
+Unlike current systems such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], that derive a probability distribution from a program, in our system some choices are represented by a parameter that can be later estimated from further information, eg observations. This approach enables later refinement and scoring of a partial program of a model from additional evidence.
+
+In [8] we address the problem of extending probability from the total choices of an ASP program to the stable models, and from there to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how ASP with probability annotated facts, formally Stochastic Answer Set Programs (SASP), can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+Main goals to be addressed
+
+Applications of this process include assigning a score to a SASP with respect to the empiric distribution of a given dataset. In turn, this score can be used by evolutionary algorithms searching for optimal models of that dataset. 
+
+This makes possible to induce a probabilistic model (a SASP) of observations based and respecting formalized BK. A declarative model of a dataset, expressed in terms of objects and rules of a formal BK, possibly setup from expert knowledge. Such kind of models explain the observations in a (first order) language that, in principle, can be read and interpreted by humans, thus addressing the problem of Explainable Artificial Intelligence (XAI).
+
+Another potential advantage of our approach is that induction of logic programs is usually achieved with small datasets. 
+
+Therefore, the driver of this project that frames the tasks, milestones and main objectives is the use of SASP and the study of induction of SASP from BK and observations.
+
+Task "Structure and Induction of SASP (SI)" main goal is a theoretical study for induction of SAPS. It continues the work of [8] by clarifying the role of SASP structure and composition elements (eg stratified or recursive programs, functional symbols) in the stable models, the equivalence relation of events and, from there, proceed to the study of induction of SASP using program space exploration algorithms based on program transformation rules (eg genetic algorithms).
+
+Task "Integration with existing ASP and ILP software frameworks (INT)" main goal is the implementation of software tools to use and induce SASP. This task is expected to benefit from the theoretical research of the previous task and its results to be used, by non-specialist researchers, in future applications.
+
+Task "High Performance Computing for Induction and Use of SASPs (HPC)" main goal is the speed-up and scale-up of use and induction of SASP using distributed HPC systems. It should benefit from the theoretical work of the first task and from some output of the second task. The expected outcome of this task is set of prototype programs and/or libraries exploring complex knowledge bases or large datasets. 
+
+Task "Applications of SASPs (APP)" main goal is the application of SASP to theoretical and real-world problems. This task is expected to benefit from the software tools from the second and third tasks. In the end, we should get an assessment of the performance of hand-coded and induced SASPs with respect to selected theoretical and real-world problems.
+
+Knowledge and skills available in the group
+
+Francisco Coelho has a PhD in Computer Science and MSc in Mathematics. His main research work deals with the interplay of statistical and logic AI and he has contributed to/with software supporting research work in the areas of machine learning, agent based simulations and combinatorial game theory.
+
+Bruno Dinis has a PhD in Mathematics. He has written over 20 papers on several aspects of logic, for the most part in proof interpretations and its applications (proof mining).
+
+Salvador Abreu [TODO]
+
+Miguel Avillez [TODO]
+
+Strategy and methodologies to be used
+
+The strategic path 
+
+Novelty and the expected results
+
+## State of the art and Objectives (6000)
+
+> In this section, the PI must provide an overview of his/her research field, present the state of the art of the research area in connection with the ground-breaking nature and potential impact of the proposed research project. References to the PI’s previous work should be included. The PI should focus on the following questions:
+> - To what extent does the proposed research **address important challenges**?
+> - To what extent are the **objectives ambitious and beyond the state of the art** (e.g. novel concepts and approaches or development between or across disciplines)?
+
+Theoretical state of the art and Objectives
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Here we aim to explore how Answer Set Programs (ASP) with probabilistic facts can lead to characterizations of probability functions on the program's domain, which is not straightforward in the context of ASP (see [1, 2, 3, 4]).
+
+Unlike current systems such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], that derive a probability distribution from a program, in our system some choices are represented by a parameter that can be later estimated from further information, eg observations. This approach enables later refinement and scoring of a partial program of a model from additional evidence.
+
+In [8] we address the problem of extending probability from the total choices of an ASP program to the stable models, and from there to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how ASP with probability annotated facts, formally Stochastic Answer Set Programs (SASP), can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+While the representation of arbitrary bayesian networks conferes to SASP the capability to represent a very large collection of problems, the problem of obtaining such SASP remains open. 
+
+To address it we are intent to utilize the score of an SASP with respect to a dataset (ie evidence), that we introduced and illustrated in [8], to guide evolutionary algorithms exploring a space of programs, thus inducing SASP from evidence and background knowledge.
+
+This is an ambitious objective that we plan to follow with this project by studying (1) the effects of program structure and composition, (2) program transformation rules in task "Structure and Induction of SASP (SI)" and in tasks (3) "Integration with existing ASP and ILP software frameworks (INT)" and (4) "High Performance Computing for Induction and Use of SASP (HPC)". These tasks should provide software tools to use and induce SASP, the former task for general use and the former utilizing distributed HPC to speed-up and scale-up applications of SASP.  
+
+Current systems ([3, 5, 6, 7]) adhere to a semantic of probabilistic logic programs different from ours. Therefore, it is necessary to provide a set of software tools to use and induce SASP.
+
+Application state of the art and Objectives
+
+
+## Research plan and methods (10000)
+
+> In this section, the PI should describe the proposed research plan and the methodologies to be used, focusing on the following questions:
+> - To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
+> - To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
+> - To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
+> 
+> Funded projects will now have access to advanced computer resources and research data repositories provided by FCT without the need for further scientific evaluation. This includes computing time in FCT's two new supercomputers, Deucalion and MareNostrum 5. To this end, FCT kindly requests that applicants answer two simple yes/no additional questions:
+> - Identify whether the work plan requires advanced computer resources to be provided by FCT.
+> - Identify whether the work plan requires space in a research data repository to be provided by the FCT.
+
+
+## Bibliographic References (1000)
+
+> This section is intended to include the references cited in the state of art and in the research plan and methods, with a cross-referencing methodology chosen by the PI, namely: APA, MLA or Chicago.
+> 
+> The following elements are considered for each reference: title; authors' names in the order in which they appear in the publication; name of the book or journal; editorial data, where applicable; volume number; page numbers; year of publication. If the publications are available electronically, you can add their URL, although this is not mandatory.
+> 
+> Bibliographical references are not limited to the PI and team members' publications.
+
+1. Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: Semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239.
+2. Verreet, V., Derkinderen, V., Dos Martires, P. Z., & De Raedt, L. (2022, June). Inference and learning with model uncertainty in probabilistic logic programs. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 9, pp. 10060-10069).
+3. Baral, C., Gelfond, M., & Rushton, N. (2009). Probabilistic reasoning with answer sets. Theory and Practice of Logic Programming, 9(1), 57-144.
+4. Pajunen, J., & Janhunen, T. (2021). Solution enumeration by optimality in answer set programming. Theory and Practice of Logic Programming, 21(6), 750-767.
+5. De Raedt, L., Kimmig, A., & Toivonen, H. (2007). ProbLog: A probabilistic Prolog and its application in link discovery. In IJCAI 2007, Proceedings of the 20th international joint conference on artificial intelligence (pp. 2462-2467). IJCAI-INT JOINT CONF ARTIF INTELL.
+6. Lee, J., & Wang, Y. (2016, March). Weighted rules under the stable model semantics. In Fifteenth international conference on the principles of knowledge representation and reasoning.
+7. Alberti, M., Bellodi, E., Cota, G., Riguzzi, F., & Zese, R. (2017). cplint on SWISH: Probabilistic logical inference with a web browser. Intelligenza Artificiale, 11(1), 47-64.
+8. Coelho, F., Dinis, B., & Abreu, S. (2024).  An Algebraic Approach to Stochastic ASP. Submitted.
+9.  Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+10. López, J., Múnera, D., Diaz, D., & Abreu, S. (2018). Weaving of metaheuristics with cooperative parallelism. In Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part I 15 (pp. 436-448). Springer International Publishing.
+
+## Past publications (WAITING)
+
+[1] Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+[2] Codognet, Philippe, Daniel Diaz, and Salvador Abreu. "Quantum and Digital Annealing for the Quadratic Assignment Problem." 2022 IEEE International Conference on Quantum Software (QSW). IEEE, 2022.
+[3] Eloy, Eduardo, Vladimir Bushenkov, and Salvador Abreu. "Constraint Modeling for Forest Management." International Conference on Dynamic Control and Optimization. Cham: Springer International Publishing, 2021.
+[4] López, Jheisson, et al. "Weaving of metaheuristics with cooperative parallelism." Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, 2018, Proceedings, Part I 15. Springer International Publishing, 2018.
+[5] Codognet, P., Munera, D., Diaz, D. and Abreu, S., 2018. Parallel local search. Handbook of parallel constraint reasoning, pp.381-417
+
+## Tasks (DONE)
+
+## Project timeline and management
+
+### Timeline (DONE)
+
+### Management (3000)
+
+> in this section, the PI should include a description of the project management structure to be adopted, in particular the coordination between participants, the meetings planned and the reporting structure. The proposed structure will depend on the size of the project and, in particular, the existence of participants from different research units.
+
+## Ethical issues (DONE)
+
+## 2030 Agenda (3000)
+
+> The Sustainable Development Goals (SDGs) and the 2030 Agenda, adopted by almost all countries in the world, in the context of the United Nations, define the priorities and aspirations of global sustainable development for 2030 and seek to mobilize global efforts around a set of common goals and objectives.
+> 
+> There are 17 SDGs, in areas that affect the quality of life of all citizens of the world and those who are yet to come.
+> 
+> In this section the PI should identify one, or up to a maximum of three, of the 17 Sustainable Development Goals of the United Nations 2030 Agenda and justify how the application fits into the selected SDGs.
+
+
+## Other projects (DONE)
+
+## Attachments (DONE)
+
@@ -0,0 +1,39 @@
+tarfea gestão e coordenação
+tarefa inicial - leavantamento estado arte e ferramentas
+
+tarefa INT -> protótico post-doc
+
+virtual machine migration and server consolidation in datacenters energy, miguel 
+
+CV narrativo do IR
+
+Substituir os acrónimos pelos nomes. O avaliador não sabe o que é FCUL, UL, UÉ, etc...
+
+"1997.... About Hilbert's..." devia ser "on Hilbert's...".
+
+O mesmo em 2006.
+
+Remover "2006-2021, Period of minor visible activity... "
+
+Substituir 2008... a 2017 por um único período "2006-2021 - research and teaching activity on... with several publications, e.g., articles and books."
+
+"2021-... Research member of the High Performance Computing Chair (HPC Chair).
+
+"2021-... Preparation and lecturing of training courses on .... under the HPC Chair and the european projects EuroCC and EuroCC2, funded by  the European Commission - EuroHPC Joint Undertaking."
+
+2022 PI (Investigador Responsável= of the project REFERENCIA, FCT, Portugal
+
+Contribuições para o desenvolvimento de competências ao nível individual e/ou em equipas
+
+Mudar "teacher" por lecturer or professor
+
+
+Que relevância atribui a este financiamento para a fase atual da sua carreira e/ou do seu percurso de investigação?
+
+By then my unclear research goal become how to combine the strengths of statistical and logic AI.
+
+Esta frase é assassina de ti próprio. Estiveste a dar um tiro no que andaste a fazer.
+
+Other issues interrupted this research.
+
+Hein?
@@ -0,0 +1,30 @@
+# Research team CV synopsis
+
+- Francisco Coelho completed his PhD in Informatics in 2006 at Universidade de Lisboa under the supervision of Helder Coelho on Artificial Intelligence. Is previous formation is on Mathematics, where he has a Master degree in Mathematics, specialty Algebra, with a dissertation about Hilbert's tenth problem and about geometric computation, advised by Prof. Augusto Franco de Oliveira and Prof. José Félix Costa.
+
+Currently he is Assistant Professor at the Computer Science department of Universidade de Évora, where he has coordinated more than twenty courses and restructured or proposed other six, to the graduation and master degrees. He is supervising three PhD thesis and two MSc dissertations and has supervised other six completed MSc dissertations.
+
+He contributed with software and writing to papers covering a wide range of subjects but mostly about logic and statistical AI. He is integrated member of the Intelligent Systems of the research unit NOVALINCS and member of the scientific team of the High Performance Computing Chair.
+
+- Bruno Dinis completed his PhD in Maths in 2013 at the University of Évora under the supervision of Imme van den Berg on Nonstandard Analysis.
+
+After his doctoral studies, he was a postdoc at the Faculdade de Ciências under the supervision of Fernando Ferreira, working on Proof Theory.
+
+Bruno Dinis is currently an Assistant Professor at the Universidade de Évora. Co-supervised 1 master's dissertation.
+
+He has written over 20 papers on several aspects of logic, for the most part in proof interpretations and its applications (proof mining).
+
+- Salvador Abreu is Full Professor at the University of Évora (UE) School of Science and Technology since 2013, Senior Researcher at NOVA LINCS and President of the Scientific Council at the UE Institute for Research and Advanced Training (IIFA). He currently directs the PhD Program in Informatics at UE.
+
+He holds a Habilitation in Informatics from the University of Évora (2009), a PhD in Informatics from Universidade NOVA de Lisboa (1994), and a BSc in Informatics Engineering from Universidade Nova de Lisboa (1987).
+
+Salvador successfully supervised 9 doctoral theses and is currently directing 3. He was granted an IBM SUR award in 2013 and a JSPS Invitation Fellowship in 2015. He participates or participated as a project member or Principal Investigator in nationally and European funded projects, including OAR, AJACS, STAMPA, JEDI, HORUS, VAPS, BIOECOSYS, AI4EU, EUGREEN and PaCoMoCo.
+
+- Miguel Avillez (PhD in Astrophysics) is a tenured research full professor in Astrophysics at the Institute for Research and Advanced Training, University of Évora, being the Chair-holder of the High Performance Computing Chair. He is a guest professor at the Department of Astronomy and Astrophysics of the Technical University Berlin, Germany. He is the director of the High Performance Computing Centre of the University of Évora that houses the the OBLIVION Supercomputer. His research focuses on theoretical and computational astrophysics, computational atomic physics, and numerical analysis, studying the evolution of the interstellar medium in galaxies, the stars life cycle, the circulation of matter between the disks and galactic halos, and, more recently, the distribution of elements in the first galaxies formed after the Big Bang. In addition he is deeply involved in software development, refactoring and acceleration to take advantage of supercomputing facilities and exascale computing. 
+
+His research over the years has been funded by, e.g., the National Science Foundation (US), American Museum of Natural History (US), Compaq (US), Portuguese Science Foundation, European Commission, European Science Foundation, DFG, European Space Agency, and NASA.
+
+Over the years he has been involved in scientific working groups of major international projects, some related to the construction of space telescopes (e.g., WSO-UV, Athena, SIRIUS), and led/leads international consortia in, e.g., computational astrophysics, supercomputing in astrophysical fluid flow, and on HPC & HPDA (2019-2023) and HPC, HPDA & AI (2021-2027). He participated in the PRACE (Partnership for Advanced Computing in Europe; 2011-2021), EuroCC (National Competence Centres in the framework of EuroHPC; 2020-2022). Currently leads the WP6 (High Performance Computing) of the research infrastructure ENGAGE SKA, the Task 19.2 "Training and Awareness" of the NCC Portugal in EuroCC2 (EuroHPC JU) and the WP3 "Training" in the ATTRACT European Digital Innovation Hub, as well, as the ERASMUS+ Advanced Computing Consortium that involves 14 higher education institutions in Portugal. He was the european Benchmark Code Owner of the GADGET software (versions 2 through 4) under PRACE (2017-2021) and is European Training Champion for the projects EuroCC and EuroCC2.
+
+Publishes regularly in top journals in his field and in the Nature journal.
+
-# Tasks
  
-## Task List
+<!--
+- **Project timeline and management.** list of milestones, the timeline and the description of the management structure
+  - **Milestones list**
+    - milestone = objective achieved; phase completed; result obtained
+    - include what can be demonstrated or reported on that date
+    - up to 6 milestones
+    - select tasks associated with the milestone
+    - mark milestones on the **timeline**.
+  - **Timeline**
+    - start with the available spreadsheet
+    - upload "timeline.pdf"
+    - Indicate **partner responsible for task**; **acronyms of partners involved**
+  - **Management** project management structure: coordination; meetings; reporting structure
  
-### Task LPSP
+-->
+
+<!-- 
+### Task APPS
  
 - **Denomination**
-  -  Logic Programs Structure and Properties
-- **Description and expected results:**
-    - **Objectives**: Clarify the role of logic program structure, eg stratified, or recursive  programs or functional symbols, in the equivalence relation of events classes. 
-    - **Methods**: Investigate the types of logic program structures, how they affect known ILP systems and what is the relationship with our approach.
-    - **Expected Results**: Two papers accepted in A* or A international conferences or Q1 journals.
+  - Applications of SASPs in Statistic Tasks
+- **Description and expected results**
+    - **Objectives**: [TODO]
+    - **Methods**: [TODO]
+    - **Expected results**: [TODO]
     - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: Members should present the results in international conferences, requiring support for registration, travel, accommodation and food.
-- **Assigned team members:**
-  - Francisco Coelho, Universidade de Évora
-  - Bruno Dinis, Universidade de Évora
-  - Salvador Abreu, Universidade de Évora
-- **Person*Month:**
+    - **Partners and Institution roles**: Universidade de Évora [TODO] [ROLES]
+    - **Justification for the needed resources**: [TODO]
+- **Assigned team members**
+  - [TODO] Member
+- **Person * Month**
   - [TODO]
-- **Deliverables:**
-  - Paper ONE in International Conference: M08
+- **Deliverables**
+  - [TODO]Type  and Description; evidences and results
 - **Budget**
-  - Registration, travel, accommodation and food for conference ONE: 3000,00€
-  - Total, including 25% overheads: 3750,00€
+  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
+  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+-->
  
-### Task LPEQ
+
+<!-- 
+### Task RWC
  
 - **Denomination**
-  - The Role of Equivalence Relations in Scoring Programs
+  - Applications of SASPs to Real World Cases 
 - **Description and expected results**
-    - **Objectives**: Clarify the role of the equivalence relation, used to partition the event space, in the performance of methods and applications. 
-    - **Methods**: Investigate variations of the equivalence relation, eg considering only super-events instead of super- and sub-events, and the resulting effects.
-    - **Expected Results**: One paper accepted in A* or A international conference or Q1 journal.
-    - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: A member should present the results in an international conference, requiring support for registration, travel, accommodation and food.
+    - **Objectives**: Apply SASP, and SASP induction, to some real world cases described in the relevant literature (eg [TODO]).
+    - **Methods**: Gather information in the form of background knowledge (eg from experts) and data (positive and negative examples) about the selected problem; Evaluate hand-coded and induced SASPs in that problem; Compare with other approaches to that problem. 
+    - **Expected results**: Assessment of the performance of hard-coded and induced SASPs on the selected problem; List of advantages and problems.
+    - **Links to other tasks**:
+      - Preconditions from other tasks: Libraries, and respective documentation, from tasks IFS and HPC.
+      - Results for other tasks: None - This is a final task.
+    - **Partners and Institution roles**:
+      - Universidade de Évora, Principal contractor;
+    - **Justification for the needed resources**:  
+      - A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
+      - An HPC system is required to this task.
 - **Assigned team members**
   - Francisco Coelho, Universidade de Évora
-  - Bruno Dinis, Universidade de Évora
-- **Person*Month**
-  - [TODO]
+  - [TODO], [TODO]
+- **Person * Month**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   6    | 1.0 |
+  | [TODO]           |      16.7% |   6    | 1.0 |
+  | **Total**        |            |        | 2.0 |
 - **Deliverables**
-  - Paper TWO in International Conference: M09 - M17
+  - A paper accepted in a A* or A international conference or Q1 journal, by 2026-03-01.
 - **Budget**
-  - Registration, travel, accommodation and food for conference TWO: 3000,00€
-  - Total, including 25% overheads: 3750,00€
+  | Item                                                       |   Amount |
+  |------------------------------------------------------------|---------:|
+  | Registration, travel, per diem in international conference | 3000.00€ |
+  | HPC system                                                 |  500.00€ |
+  | Overheads (25%)                                            |  875.00€ |
+  | **Total**                                                  | 4375.00€ |
+  
+-->
+
+<!-- 
  
-### Task LPERR
+### Task TaskID
  
 - **Denomination**
-  - The Role of the Error Function
+  - [TODO] concise and self-explanatory
 - **Description and expected results**
-    - **Objectives**: Explore the role of the error function, used to score a probabilistic ASP wrt observations, in the performance of methods and applications.
-    - **Methods**: Investigate variations of the error function, eg Kullback-Leibler divergence instead of the L2 used, observation sets form various domains, and the resulting effects.
-    - **Expected Results**: One paper accepted in A* or A international conference or Q1 journal.
+    - **Objectives**: [TODO]
+    - **Methods**: [TODO]
+    - **Expected results**: [TODO]
     - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: A member should present the results in an international conference, requiring support for registration, travel, accommodation and food.
+    - **Partners and Institution roles**: Universidade de Évora [TODO] [ROLES]
+    - **Justification for the needed resources**: [TODO]
 - **Assigned team members**
-  - Francisco Coelho, Universidade de Évora
-  - Ligia Henriques-Rodrigues, Universidade de Évora
-- **Person*Month**
+  - [TODO] Member
+- **Person * Month**
   - [TODO]
 - **Deliverables**
-  - Paper THREE in International Conference: M01 - M08
+  - [TODO]Type  and Description; evidences and results
 - **Budget**
-  - Registration, travel, accommodation and food for conference THREE: 3000,00€
-  - Total, including 25% overheads: 3750,00€
+  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
+  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates" 
+ 
+-->
  
-### Task ISASTSE
+<!--
+### Task LP.ERR
  
 - **Denomination**
-  - Inductive Stochastic Answer Set Programs by Space Exploration
+  - The Role of the Error Function
 - **Description and expected results**
-    - **Objectives**: Proceed from scoring programs to induce ASP programs using genetic algorithms or other program space exploration methods.
-    - **Methods**: Investigate program transformation and program space exploration methods and rules.  
-    - **Expected Results**: One paper accepted in A* or A international conference or Q1 journal.
+    - **Objectives**: Explore the role of the error function, used to score a probabilistic ASP wrt observations, in the performance of methods and applications.
+    - **Methods**: Investigate variations of the error function, eg Kullback-Leibler divergence instead of the L2 used, observation sets form various domains, and the resulting effects.
+    - **Expected results**: One paper accepted in A* or A international conference or Q1 journal.
     - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**:  A member should present the results in an international conference, requiring support for registration, travel, accommodation and food.
+    - **Partners and Institution roles**: Universidade de Évora [TODO] [ROLES]
+    - **Justification for the needed resources**: A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
 - **Assigned team members**
   - Francisco Coelho, Universidade de Évora
-  - Salvador Abreu, Universidade de Évora
-- **Person*Month**
+  - Ligia Henriques-Rodrigues, Universidade de Évora
+- **Person * Month**
   - [TODO]
 - **Deliverables**
-  - Paper FOUR in International Conference: M01 - M09
+  - Paper THREE in International Conference: M01 - M08
 - **Budget**
-  - Registration, travel, accommodation and food for conference FOUR: 3000,00€
-  - Total, including 25% overheads: 3750,00€
+  - Registration, travel, per diem for conference THREE: 3000.00€
+  - Total, including 25% overheads: 3750.00€
+-->
  
-### Task ISF
+
+<!--
+### Task LP.EQ
  
 - **Denomination**
-  - Integration with existing ASP and ILP software frameworks
+  - Equivalence Relations in Scoring Programs
 - **Description and expected results**
-    - **Objectives**: Exploit and contribute to existing ASP frameworks, such as Potassco.
-    - **Methods**: Implement a library to parse the ASP language extended with probabilistic annotations; utilize existing ASP frameworks to compute stable models; compute the event classes and respective probabilities.
-    - **Expected Results**: A library, and the respective API, to parse extended ASP; interface with existing ASP frameworks; compute event classes and respective probabilities.
-    - **Links to other tasks**: 
-      - Result: Task HPC; deliverable: Library API
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**:
-      - The implementation amount and complexity requires a fulltime PhD student working over a year, using a suitable laptop.
+    - **Objectives**: Clarify the role of the equivalence relation, used to partition the event space, on the performance of algorithms related to classes and respective probabilities. 
+    - **Methods**: Investigate variations of the equivalence relation (eg, considering only super-events instead of super- and sub-events) and the resulting effects on algorithms related to classes and respective probabilities.
+    - **Expected results**: Assessment on the effects of the variations of the equivalence relation on algorithms related to classes and respective probabilities.
+    - **Links to other tasks**:
+      - Preconditions from other tasks: 
+        - SI: Program structure and composition elements, assessed in task SI, contribute to determine the stable models that are, in turn, used to define the equivalence relation, studied here. 
+      - Results for other tasks: 
+        - APP and RWC - The equivalence relation associates certain events to certain stable models and from this association results event probability. In applications, either theoretical scenarios or real world cases, models (in this case, SASPs) must support the calculus of event probabilities.
+    - **Partners and Institution roles**:
+      - Universidade de Évora, Principal contractor;
+    - **Justification for the needed resources**: A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
 - **Assigned team members**
   - Francisco Coelho, Universidade de Évora
-  - BI Scholarship fellow, Universidade de Évora
-- **Person*Month**
-  - [TODO]
+  - Bruno Dinis, Universidade de Évora
+- **Person * Month**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   6    | 1.0 |
+  | Bruno Dinis      |      16.7% |   6    | 1.0 |
+  | **Total**        |            |        | 2.0 |
 - **Deliverables**
-  - Software Library Repository: M03 - M15
-  - Library API:  M06
-  - Implementation Report: M16
+  - A paper accepted in a A* or A international conference or Q1 journal, by 2026-02-01.
 - **Budget**
-  - Laptop computer:   2600,00€
-  - BI Scholarship:   13735,68€ = 1144,64€ x 12 months 
-  - Total, including 25% overheads: 20419,60€
+  | Item                                                       |   Amount |
+  |------------------------------------------------------------|---------:|
+  | Registration, travel, per diem in international conference | 3000.00€ |
+  | Overheads (25%)                                            |  750.00€ |
+  | **Total**                                                  | 3750.00€ |
+-->
  
-### Task HPC
+
+<!-- 
+### Task ISE
  
 - **Denomination**
-  - High Performance Computing for Induction and Use of SASP
+  - Inductive Stochastic Answer Set Programs by Space Exploration
 - **Description and expected results**
-    - **Objectives**: Use High Performance Computing systems to speedup and scale-up applications of our methods.
-    - **Methods**: Benchmark the benefits of data and process distribution on High Performance Computing systems. 
-    - **Expected Results**: Report on the performance of the distributed versions of the programs to interface with existing ASP frameworks and compute event classes and respective probabilities.  
+    - **Objectives**: Proceed from already established (in existing research) scoring programs methods to induce Stochastic Answer Set Programs (SASPs) using program space exploration algorithms based on program transformation rules (eg genetic algorithms).
+    - **Methods**: Investigate program transformation rules and program space exploration algorithms in the context of SASPs.  
+    - **Expected results**: Compilation and assessment of program transformation rules and space explorations algorithms for SASPs.
     - **Links to other tasks**:
-      -  Precondition: Task ISF; Deliverable: Library API
-    - **Partners and Institution Roles**: 
-      - Universidade de Évora [ROLES]
-      - High Performance Computing Chair [ROLES]
-    - **Justification for the needed resources**: [TODO]
+      - Preconditions from other tasks: None - this is an initial task, a continuation of already done research;
+      - Results for other tasks: 
+        - HPC, APP, RWC: This is an algorithm oriented research task; its results are to be utilized by the subsequent application tasks: HPC for induction and use of SASPs (HPC), Application of SASPs in Theoretic Scenarios (APP) and Applications of SASPs to Real World Cases (RWC). 
+        - INT: Induction of SASPs from data and background knowledge, in task INT, requires the assessments of program space exploration algorithms and program transformation rules.
+    - **Partners and Institution roles**:
+      - Universidade de Évora, Principal contractor;
+    - **Justification for the needed resources**: A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
 - **Assigned team members**
   - Francisco Coelho, Universidade de Évora
-  - Miguel Avillez, High Performance Computing Chair
-- **Person*Month**
-  - [TODO]
+  - Salvador Abreu, Universidade de Évora
+- **Person * Month**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   6    | 1.0 |
+  | Salvador Abreu   |      16.7% |   6    | 1.0 |
+  | **Total**        |            |        | 2.0 |
 - **Deliverables**
-  - Software Library Repository: M06 - M18
-  - Implementation Report: M18
+  - A paper accepted in a A* or A international conference or Q1 journal, by 2025-03-01.
 - **Budget**
-  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
-  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+  | Item                                          |   Amount |
+  |-----------------------------------------------|---------:|
+  | Registration in international conference (x2) | 1400.00€ |
+  | Travel to international conference (x2)       | 1000.00€ |
+  | Per diem international conference (x3x2)      | 1152.00€ |
+  | Overheads (25%)                               |  888.00€ |
+  | **Total**                                     | 4440.00€ | -->
+
+# Tasks
+
+## Task List
  
-### Task APPT
+### Task SI
  
 - **Denomination**
-  - Applications of Stochastic ASP in Theoretic Scenarios
-- **Description and expected results**
-    - **Objectives**: [TODO]
-    - **Methods**: [TODO]
-    - **Expected Results**: [TODO]
-    - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: [TODO]
-- **Assigned team members**
-  - [TODO] Member
-- **Person*Month**
-  - [TODO]
-- **Deliverables**
-  - [TODO]Type  and Description; evidences and results
+  -  Structure and Induction of SASP (SI)
+- **Description and expected results:**
+  - **Objectives**: Clarify the role of Stochastic Answer Set Programs (SASPs) structure and composition elements (eg stratified or recursive  programs, functional symbols) in the stable models, our equivalence relation of events, and existing ASP and ILP systems; Proceed from already established (in existing research) scoring programs methods to SASPs using program space exploration algorithms based on program transformation rules (eg genetic algorithms). 
+  - **Methods**: Investigate SASP structures and composition elements, how they affect stable models, event classes, and respective probability; Investigate program transformation rules and program space exploration algorithms in the context of SASPs.
+  - **Expected results**: Assessment on the effects of the studied structures and composition elements on  stable models, event classes, and respective probability; Compilation and assessment of program transformation rules and space explorations algorithms for SASPs.
+  - **Links to other tasks**:
+    - Preconditions from other tasks: None - this is an initial task, a continuation of already done research;
+    - Results for other tasks: 
+      - INT, HPC: This task gives important insights into algorithm design and implementation,  for the computation of the event classes and respective probabilities, either in a sequencial setting (INT task) or distributed (HPC task).
+  - **Partners and Institution roles**: 
+    - Universidade de Évora, Principal contractor;
+  - **Justification for the needed resources**: A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
+- **Assigned team members:**
+  - Francisco Coelho, Universidade de Évora;
+  - Salvador Abreu, Universidade de Évora;
+  - Bruno Dinis, Universidade de Évora;
+- **Start Date:** 2024-09-01
+- **Duration (months):** 6
+- **Person * Month:**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   6    | 1.0 |
+  | Salvador Abreu   |      16.7% |   6    | 1.0 |
+  | Bruno Dinis      |      16.7% |   6    | 1.0 |
+  | **Total**        |            |        | 3.0 |
+- **Deliverables:**
+  - Two papers accepted in A* or A international conferences or Q1 journals, by 2025-03-01.
 - **Budget**
-  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
-  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+  Registration in international conference (x2) , 1400.00€
+  Travel to international conference (x2)       , 1000.00€
+  Per diem international conference (x3x2)      , 1152.00€
+  Overheads (25%)                               ,  888.00€
+  **Total**                                     , 4440.00€
  
-### Task APPS
+### Task INT
  
 - **Denomination**
-  - Applications of Stochastic ASP in Statistic Tasks
+  - Integration with existing ASP and ILP software frameworks (INT)
 - **Description and expected results**
-    - **Objectives**: [TODO]
-    - **Methods**: [TODO]
-    - **Expected Results**: [TODO]
-    - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: [TODO]
+    - **Objectives**: A library, and its documentation, to enable efficient SASP related computations: parsing, event classes and probabilities, induction.
+    - **Methods**: Implement, test, document and demonstrate a library to process SASP programs (parse the SASP language; utilize existing ASP frameworks to compute stable models; compute the event classes and respective probabilities; induce SASPs from data).
+    - **Expected results**: A library that implements the algorithms proposed in previous tasks and existing research, to be utilized in future applications and tasks, and associated documentation; A PhD graduation; Contributions to existing ASP frameworks, such as Potassco. 
+    - **Links to other tasks**: 
+      - Preconditions from other tasks: None - this is an initial task, a continuation of already done research; However, results from task SI will guide the implementation for induction of SASPs from data and background knowledge.
+      - Results for other tasks: 
+        - HPC: A proposed library API, to guide the implementation in the HPC task.
+        - APP: This applied task requires adequate software support, ie the library and documentation delivered by this task. 
+    - **Partners and Institution roles**:
+      - Universidade de Évora, Principal contractor;
+    - **Justification for the needed resources**: The implementation volume and complexity requires a fulltime PhD student working over a year, using a suitable laptop; The PhD student should present the results of this task in an international conference, requiring support for registration, travel, per diem.
 - **Assigned team members**
-  - [TODO] Member
-- **Person*Month**
-  - [TODO]
+  - Francisco Coelho, Universidade de Évora;
+  - BI Scholarship fellow, Universidade de Évora;
+- **Start Date:** 2024-12-01
+- **Duration (months):** 12
+- **Person * Month**
+  | Member                | Percentage | Months |  P*M |
+  |-----------------------|-----------:|:------:|-----:|
+  | Francisco Coelho      |      16.7% |   12   |  2.0 |
+  | BI Scholarship fellow |     100.0% |   12   | 12.0 |
+  | **Total**             |            |        | 14.0 |
 - **Deliverables**
-  - [TODO]Type  and Description; evidences and results
+  - Proposal for the library API, by 2025-03-01.
+  - Report documenting the features and progress in the library implementation, by 2025-06-01.
+  - Paper accepted in a A* or A international conference or Q1 journal, by 2025-09-01.
+  - Library, and the respective documentation, to parse SASP; interface with existing ASP frameworks; compute event classes and respective probabilities, by 2025-06-01.
+  - Completed PhD thesis, by 2025-12-01.
 - **Budget**
-  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
-  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+  | Item                                         |    Amount |
+  |----------------------------------------------|----------:|
+  Laptop Computer (i7; 32GB RAM; 1TB SSD; 15")  2658.21€
+  Registration in international conference       700.00€
+  Travel to international conference            1000.00€
+  Per diem international conference (x3)         576.00€
+  BI Scholarship (12 months, 1144.64€/month)   13735.68€
+  Overheads (25%)                               4667.47€
+  **Total**                                    23337.36€
  
-### Task APPW
+### Task HPC
  
 - **Denomination**
-  - Applications of Stochastic ASP in Real World Cases 
+  - High Performance Computing for Induction and Use of SASPs (HPC)
 - **Description and expected results**
-    - **Objectives**: [TODO]
-    - **Methods**: [TODO]
-    - **Expected Results**: [TODO]
-    - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: [TODO]
+    - **Objectives**: Use High Performance Computing systems to speedup and scale-up applications of SASPs.
+    - **Methods**: Benchmark the benefits of data and process distribution for SASPs on High Performance Computing systems. 
+    - **Expected results**: Compilation and assessment of distributed SASPs on HPC systems; A library that implements distributed versions of some API functions described in the INT task, to be utilized in future applications and tasks, and associated documentation; 
+    - **Links to other tasks**:
+      - Preconditions from other tasks: 
+        - INT: The proposed library API is utilized to guide this task implementation, in order to strive for compatibility.
+        - SI: Results from task SI will guide the implementation for induction of SASPs from data and background knowledge.
+      - Results for other tasks:
+        - APP: This applied task requires adequate software support, ie the library and documentation delivered by this task.
+    - **Partners and Institution roles**: 
+      - Universidade de Évora, Principal contractor;
+      - High Performance Computing Chair, Research Unit;
+    - **Justification for the needed resources**: 
+      - A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
+      - Adaptation of sequential programs to HPC systems requires expert consultation.
+      - An HPC system is required to this task.
 - **Assigned team members**
-  - [TODO] Member
-- **Person*Month**
-  - [TODO]
+  - Francisco Coelho, Universidade de Évora
+  - Miguel Avillez, High Performance Computing Chair (as Consultant)
+- **Start Date:** 2025-03-01
+- **Duration (months):** 12
+- **Person * Month**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   12   | 2.0 |
+  | Miguel Avillez   |      16.7% |   12   | 2.0 |
+  | **Total**        |            |        | 4.0 |
 - **Deliverables**
-  - [TODO]Type  and Description; evidences and results
+  - Report on the performance of the distributed versions of the programs to interface with existing ASP frameworks and compute event classes and respective probabilities, by 2025-09-01.
+  - A library or set of programs for distributed evaluation of SASP on HPC systems, by 2025-12-01. 
+  - Paper accepted in a A* or A international conference or Q1 journal, by 2026-03-01.
 - **Budget**
-  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
-  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+  | Item                                     |   Amount |
+  |------------------------------------------|---------:|
+  Registration in international conference   700.00€
+  Travel to international conference        1000.00€
+  Per diem international conference (x3)     576.00€
+  HPC system                                1000.00€
+  Overheads (25%)                            819.00€
+  **Total**                                 4095.00€
  
-### Task TaskID
+### Task APP
  
 - **Denomination**
-  - [TODO] concise and self-explanatory
+  - Applications of SASPs (APP)
 - **Description and expected results**
-    - **Objectives**: [TODO]
-    - **Methods**: [TODO]
-    - **Expected Results**: [TODO]
-    - **Links to other tasks**: [TODO] (preconditions and results)
-    - **Partners and Institution Roles**: Universidade de Évora [TODO] [ROLES]
-    - **Justification for the needed resources**: [TODO]
+    - **Objectives**: Apply SASP, and SASP induction, to some theoretic scenarios (toy problems) described in the relevant literature (eg Stochastic Plan Generation, Logic/Statistic Puzzles) as well as to some real world cases (eg [TODO]).
+    - **Methods**: Compile a set of theoretic and real-world problems; Gather information in the form of background knowledge (eg from experts) and data (positive and negative examples) about selected problems; Evaluate hand-coded and induced SASPs on that set; Compare with state-of-the-art results. 
+    - **Expected results**: Assessment of the performance of hard-coded and induced SASPs with respect to selected theoretical and real-world problems.
+    - **Links to other tasks**:
+      - Preconditions from other tasks: Libraries, and respective documentation, from tasks IFS and HPC.
+      - Results for other tasks: None - This is a final task.
+    - **Partners and Institution roles**:
+      - Universidade de Évora, Principal contractor;
+      - High Performance Computing Chair, Research Unit;
+    - **Justification for the needed resources**:  
+      - A member should present the results of this task in an international conference, requiring support for registration, travel, per diem.
+      - An HPC system is required to this task.
 - **Assigned team members**
-  - [TODO] Member
-- **Person*Month**
-  - [TODO]
+  - Francisco Coelho, Universidade de Évora
+  - Salvador Abreu, Universidade de Évora
+  - Miguel Avillez, High Performance Computing Chair
+- **Start Date:** 2025-09-01
+- **Duration (months):** 6
+- **Person * Month**
+  | Member           | Percentage | Months | P*M |
+  |------------------|-----------:|:------:|----:|
+  | Francisco Coelho |      16.7% |   6    | 1.0 |
+  | Salvador Abreu   |      16.7% |   6    | 1.0 |
+  | Miguel Avillez   |      16.7% |   6    | 1.0 |
+  | **Total**        |            |        | 3.0 |
 - **Deliverables**
-  - [TODO]Type  and Description; evidences and results
+  - A paper accepted in a A* or A international conference or Q1 journal, by 2026-03-01.
 - **Budget**
-  - [TODO] Item justification (criteria of N.4 from "Public Announcement of the Call")
-  - [TODO] Amount requested for the task: Include 25% overheads; Consistent with the _Principal Contractor Budget table in application form_; Ensure "total amount of funding requested by institution" = "total costs of the tasks in which the institution participates"
+  | Item                                     |   Amount |
+  |------------------------------------------|---------:|
+  Registration in international conference   700.00€
+  Travel to international conference        1000.00€
+  Per diem international conference (x3)     576.00€
+  HPC system                                 500.00€
+  Overheads (25%)                            694.00€
+  **Total**                                 3470.00€
+
+## Milestones
+
+### Milestone SI Two Papers
+
+- **Designação:** SI Two Papers
+- **Descrição (300):** Two papers accepted in A* or A international conferences or Q1 journals, one describing the effects of structures and composition elements on SASP on stable models, event classes, and respective probability; other describing program transformation rules and space exploration algorithms for SASPs.
+- **Tarefas:** Structure and Induction of SASPs (SI)
+- **Data:** 2025-03-01
+
+### Milestone INT API
+
+- **Designação:** INT API
+- **Descrição (300):** A proposal for the API of a library and set of programs to support the evaluation of SASP.
+- **Tarefas:** Integration with existing ASP and ILP software frameworks (INT) 
+- **Data:** 2025-03-01
+
+### Milestone INT Report
+
+- **Designação:** INT Report
+- **Descrição (300):** A report describing the implementation and documenting the use of a library and set of programs to support the evaluation of SASP.
+- **Tarefas:** Integration with existing ASP and ILP software frameworks (INT) 
+- **Data:** 2025-06-01
+
+### Milestone INT Paper
+
+- **Designação:** INT Paper
+- **Descrição (300):** A paper accepted in a A* or A international conference or Q1 journal, describing the features, strengths and limitations of a library and set of programs to support the evaluation of SASP.
+- **Tarefas:** Integration with existing ASP and ILP software frameworks (INT) 
+- **Data:** 2025-09-01
+
+### Milestone INT Library
+
+- **Designação:** INT Library
+- **Descrição (300):** A library and set of programs to support the evaluation of SASP.
+- **Tarefas:** Integration with existing ASP and ILP software frameworks (INT) 
+- **Data:** 2025-09-01
+
+### Milestone INT Thesis
+
+- **Designação:** INT Thesis
+- **Descrição (300):** A PhD thesis about SASP and a library and set of programs to support the evaluation of SASP.
+- **Tarefas:** Integration with existing ASP and ILP software frameworks (INT) 
+- **Data:** 2025-12-01
+
+### Milestone HPC Library + Report
+
+- **Designação:** HPC Library + Report
+- **Descrição (300):** A library or set of programs for distributed evaluation of SASP on HPC systems and a report organizing and documenting the use of that library. 
+- **Tarefas:** High Performance Computing for Induction and Use of SASP (HPC)
+- **Data:** 2025-12-01
+
+### Milestone HPC Paper
+
+- **Designação:** HPC Paper
+- **Descrição (300):** A paper accepted in a A* or A international conference or Q1 journal, describing compilation and assessment of distributed SASPs on HPC systems.
+- **Tarefas:** High Performance Computing for Induction and Use of SASP (HPC)
+- **Data:** 2026-03-01
+
+### Milestone APP Paper
+
+- **Designação:** APP Paper
+- **Descrição (300):** A paper accepted in a A* or A international conference or Q1 journal, assessing the performance of hard-coded and induced SASPs with respect to selected theoretical and real-world problems.
+- **Tarefas:** Applications of SASPs (APP)
+- **Data:** 2026-03-01
+
  
 ## Project Timeline
  
-```gantt
-title       IAM
+```mermaid
+gantt
+title       Induction of Stochastic Answer Set Programs by Algebraic Means (IAM)
 dateFormat  YYYY-MM-DD
+axisFormat  %Y-%m
+
+section Theoretical
+  Structure and Induction of SASPs (SI)    :si,  2024-09-01, 6M
+  SI Two Papers  :milestone, sipaper1,  2025-03-01, 0d
  
-section Tasks
+section Implementation
+  Integration with existing ASP and ILP software frameworks (INT)     :int,   2024-12-01, 12M
+  INT Library + Paper     :milestone, intpaper,   2025-09-01, 0d
+  INT Thesis    :milestone, intthesis,  2025-12-01, 0d
+  High Performance Computing for Induction and Use of SASP (HPC)     :hpc, 2025-03-01,  12M
+  HPC Library + Report  :milestone, hpclibrary, 2025-12-01, 0d
+  HPC Paper     :milestone, hpcpaper,   2026-03-01, 0d
  
-  task1   :a1, 2024-09-01, 30d
+section Application
+  Applications of SASPs (APP)    :app,  2025-09-01, 6M
+  APP Paper    :milestone, apppaper,  2026-03-01, 0d
+  #APPS   :after appt,        4M
+  #Applications of SASPs to Real World Cases (RWC)    :appw,  2025-09-01, 6M
+  #RWC Paper    :milestone, appwpaper,  2026-03-01, 0d
 ```
  
-- **Project timeline and management.** list of milestones, the timeline and the description of the management structure
-  - **Milestones list**
-    - milestone = objective achieved; phase completed; result obtained
-    - include what can be demonstrated or reported on that date
-    - up to 6 milestones
-    - select tasks associated with the milestone
-    - mark milestones on the **timeline**.
-  - **Timeline**
-    - start with the available spreadsheet
-    - upload "timeline.pdf"
-    - Indicate **partner responsible for task**; **acronyms of partners involved**
-  - **Management** project management structure: coordination; meetings; reporting structure
 \ No newline at end of file
+---
+
+Explain the participation of a post-doc student  of informatics in an task with objectives, methodologies and expected results given below.
+
+Objectives
+
+Support the application of SASP for modeling probabilistic processes and induce SASP from Background Knowledge (BK) and evidence.
+
+Methodologies and approaches
+
+Implementation (i.e., writing code according to the software design specifications), testing (i.e., verification that the implemented software functions correctly and meets the requirements outlined in the design phase), profiling (i.e., analyzing the performance of the software system to identify bottlenecks, memory leaks, and other performance issues), benchmarking (i.e., compare the performance of the software system against standard benchmarks or competitors' products) and documenting (i.e., providing comprehensive information about the software system, including its purpose, features, architecture, installation instructions, and usage guidelines): 
+    SASP intermediate representation and a parser.
+    Integration with existing, state of the art, Answer Set Program (ASP) tools such as Potassco and cplint for the computation of the stable models.
+    Instrumental functions such as: event belongs to class, class probability, event probability.
+    Support for SASP combination and transformation.
+    Integration with existing, state of the art, evolutionary explorations tools (e.g. genetic algorithms).
+    Command-line programs to support basic usage such as: list classes, query the probability of an event or class, induce SASP.
+
+Expected results
+
+A basic set of tools, including a library and command-line programs, to use Stochastic Answer Set Programs (SASP) for modeling probabilistic processes and induce SASP from Background Knowledge (BK) and evidence.
+
+
+---
+
+Consider the STATE-OF-THE-ART, the OBJECTIVES and the REFERENCES below.
+
+Rewrite the STATE-OF-THE-ART and the OBJECTIVES raking into account the given REFERENCES and possibly others.
+
+The text must have less than 5500 characters.
+
+STATE-OF-THE-ART
+
+
+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic when dealing with probabilistic phenomena, which is often the case. Probabilistic Logic Programming (PLP) is one ongoing effort to address this problem by extending the syntax and semantics of logic programs in order to have them represent and operate probability distributions (see [11]).
+
+Current systems for PLP, such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], derive a probability distribution from a program. However, for Answer Set Programs (ASP) [12] with probabilistic facts, the characterization of a probability distribution on the program's domain is not straightforward (see [1, 2, 3, 4]).
+
+In [8] we address the problem of extending probability from the total choices of an ASP program to its stable models and, from there, to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how SASP can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
+
+This representation of arbitrary bayesian networks conferes to SASP the capability to deal with a very large collection of probability problems and tasks. However, the problem of obtaining such SASP, besides hand-coded, remains open. 
+
+In our system some unknowns are represented by numeric parameters that can be estimated later from further information, e.g., evidence. This approach, delaying the assignment of certain parameters, enables later refinement and scoring a partial program from additional evidence. 
+
+In turn, scoring of SASP (i.e., models of a probabilistic phenomenon) is a key feature required to the application of evolutionary algorithms. From here we can explore how to induce SASP from BK and evidence.
+
+The calculus of the score of an SASP with respect to evidence was already introduced and illustrated in [8]. It remains to investigate the application of this process to induction of SASP from BK and evidence. 
+
+Ideas of this paper have a partial, limited, implementation, available in a public repository, that results from the work of a BII scholarship, supported by NOVALINCS "Financiamento Plurianual da unidade de I&D UIDP/04516/2020" and co-supported by Fundação para a Ciência e a Tecnologia (FCT), Portugal.
+
+In the general Induction of Logic Programs (ILP) setting (see [11, 13]) the goal is to algorithmically obtain a (target) logic program. For that, (1) BK (e.g., obtained from experts) is provided in the form of a logic program, describing objects and (first-order) relations of a domain and (2) observations are organized as positive evidence, that should be inferred from the target program, and negative evidence, that should not be inferred from the target program. Moreover, the target program must be (logically) consistent with the BK. ILP is a form of Machine Learning (ML) that offers significant advantages over numeric based ML. 
+
+For one, ILP address the problem of Explainable Artificial Intelligence (XAI) because, unlike  the large-dimensional vector based models of numeric ML, logic programs are human-readable in the sense that their declarative nature describes what objects are in the domain, their structure, properties and relations.
+Second, ILP describes phenomena with related instances while numeric ML is limited to a single (tabulated) relation where different instances (lines) are independent given the model. 
+Third, often a target program is generated from a small set of observations, while, in general, numeric ML models require large datasets to achieve significant accuracy.
+At last, expert knowledge, expressed in the BK, can be utilized to structure the target program, i.e., to model the observations. Again, this is a feature hard to achieve with numeric ML models.
+
+Drawbacks of ILP include the computational complexity of inducing the target program and the general difficulty of logic programs to deal with data with random perturbations. While the later is being addressed by PLP in general and SASP in particular, the computational complexity of induction remains an important challenge that we propose to investigate with this project.
+
+OBJECTIVES
+
+In summary, with this project we aim to continue our exploration on how SASP represent probability distributions, how to use them to model probabilistic phenomena and how they can be induced from BK and evidence.
+
+More specifically, this project's objectives are to investigate:
+
+- The role of program structure and composition in the use of PASP to model probabilistic phenomena.
+- Program transformation rules and space exploration algorithms for SASP.
+- The performance of hand-coded and induced SASP models on selected theoretic and real world cases.
+
+REFERENCES
+
+
+1. Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: Semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239.
+2. Verreet, V., Derkinderen, V., Dos Martires, P. Z., & De Raedt, L. (2022, June). Inference and learning with model uncertainty in probabilistic logic programs. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 9, pp. 10060-10069).
+3. Baral, C., Gelfond, M., & Rushton, N. (2009). Probabilistic reasoning with answer sets. Theory and Practice of Logic Programming, 9(1), 57-144.
+4. Pajunen, J., & Janhunen, T. (2021). Solution enumeration by optimality in answer set programming. Theory and Practice of Logic Programming, 21(6), 750-767.
+5. De Raedt, L., Kimmig, A., & Toivonen, H. (2007). ProbLog: A probabilistic Prolog and its application in link discovery. In IJCAI 2007, Proceedings of the 20th international joint conference on artificial intelligence (pp. 2462-2467). IJCAI-INT JOINT CONF ARTIF INTELL.
+6. Lee, J., & Wang, Y. (2016, March). Weighted rules under the stable model semantics. In Fifteenth international conference on the principles of knowledge representation and reasoning.
+7. Alberti, M., Bellodi, E., Cota, G., Riguzzi, F., & Zese, R. (2017). cplint on SWISH: Probabilistic logical inference with a web browser. Intelligenza Artificiale, 11(1), 47-64.
+8. Coelho, F., Dinis, B., & Abreu, S. (2024).  An Algebraic Approach to Stochastic ASP. Submitted.
+9.  Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
+10. López, J., Múnera, D., Diaz, D., & Abreu, S. (2018). Weaving of metaheuristics with cooperative parallelism. In Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part I 15 (pp. 436-448). Springer International Publishing.
+11. Riguzzi, F. (2022). Foundations of probabilistic logic programming: Languages, semantics, inference and learning. River Publishers.
+12. Lifschitz, V. (2002). Answer set programming and plan generation. Artificial Intelligence, 138(1-2), 39-54.
+13. Russell, S. J., & Norvig, P. (2010). Artificial intelligence a modern approach. London.
 \ No newline at end of file
@@ -0,0 +1 @@
+Subproject commit 199ef143774435c7a0883f2baf6317e8aad60223
@@ -0,0 +1 @@
+Subproject commit 2803688b6ae13c9a084b6dd3abe6b8a98964d233
-We address the problem of extending probability from the total choices of an ASP program to the standard models, and from there to general events.
+We address the problem of extending probability from the total choices of an ASP program to the stable models, and from there to general events.
 %
 Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions.
 %
@@ -0,0 +1,107 @@
+# Reviews of IJCAR24
+
+## Summary
+
+- the paper lacks clarity and maturity for a formal publication.
+  - syntax and semantics of the considered class of programs is not defined;
+  - the relation of stable models and events as well as the application of the approach is insufficiently motivated;
+  - a more thorough comparison between the proposed method and related work is missing.
+- the work is still in a very preliminary state.
+  - half of the paper is focused on developing a toy example in all its details. The space would have been better used developing deeper technical details, and exploring the advantages and limitations of the formalism.
+- the paper feels somewhat incomplete and incoherent
+  - initial issues in the presentation that could be improved (for instance, for self-containment, recall the stable model semantics and its properties, as this is central for the presented method)
+  - argument for Proposition 1 [is not] convincing [...] it should not be
+  the case that all events are disjoint.
+  - it would be insightful to not only provide the probabilities of the classes, but also of the events
+  - "testing of the prior distributions" comes a bit unexpected, and it is not fully clear what is the role.
+  - I don't see why someone would use a stochastic program to model a Bayesian network. If there is a relation, I would rather want to see a general argument, then an illustration on a simple example.
+
+
+## REVIEW 1
+
+SUBMISSION: 23
+TITLE: An Algebraic Approach to Stochastic ASP
+AUTHORS: Francisco Coelho, Bruno Dinis and Salvador Abreu
+
+----------- Overall evaluation -----------
+SCORE: -1 (weak reject)
+----- TEXT:
+The authors present an approach to define a probability distribution on events based on logic programs with probabilistic facts. As different choices for the probabilistic facts can give rise to different answer sets, parameters are introduced to capture this relation in a probabilistic sense. These parameters can later be estimated using data.    
+
+Unfortunately, the paper lacks clarity and maturity for a formal publication.
+The main issues here are that 
+1) syntax and semantics of the considered class of programs is not defined;
+2) the relation of stable models and events as well as the application of the approach is insufficiently motivated; and
+3) a more thorough comparison between the proposed method and related work is missing.
+
+
+Section 1:
+What is the precise syntactic class of programs that is considered here and how is its semantic formally defined? The introduction mentions normal programs and stable models, later disjunctions, choice rules, and weak constraints, as well as the distribution semantics are mentioned. It is stated however in Section 5 that recursion has not been considered in this work. So the scope of the contribution is unclear.
+
+What does extending a probability from total choices to cover the program domain mean? What is the program domain? 
+
+The motivation for this work is a little vague. If they goal is to find models for a dataset, what is the role of the program and what is the role of events that do not correspond to answer sets of the program? An example would be helpful. I'm in particular confused that observations can be supersets of states. 
+
+Section 2:
+There are of course proposals how to define a probability distributions on answer sets based on probabilistic facts. The relation of this proposal to such approaches and their limitations should be discussed more thoroughly.
+
+The significance of Item 2 is not clear. Also, when are observations not consistent with a program?
+
+What is described as "total choice" in the remainder of the paper has been defined as pre-total choice in the introduction.
+
+Section 3:
+The purpose of Fig. 1 is unclear without more explanation of the process that is illustrated.
+
+The abstract is not very informative without further context. Consider expanding it.
+
+
+## REVIEW 2
+
+SUBMISSION: 23
+TITLE: An Algebraic Approach to Stochastic ASP
+AUTHORS: Francisco Coelho, Bruno Dinis and Salvador Abreu
+
+----------- Overall evaluation -----------
+SCORE: -1 (weak reject)
+----- TEXT:
+This submission proposes a new probabilistic semantics for ASP programs, where the overall distribution is not pre-specified, but can be algebraically annotated and updated in presence of evidence. The semantics introduces an interplay between events and stable models.
+
+One of the main drawbacks of most probabilistic extensions of logical languages is that they tend to introduce many strong assumptions just for the sake of obtaining one, effectively computable, probability distribution. This work tries to reverse that tendency by considering just the explicit information from the program (and perhaps external observations). I found it refreshing. The way the authors deal with the lack of information (and the relation to stable models) is also, to my knowledge, novel. I have not seen similar approaches even in other probabilistic settings.
+
+Unfortunately, the work is still in a very preliminary state. The authors acknowledge that there is much to do still. In this case, half of the paper is focused on developing a toy example in all its details. The space would have been better used developing deeper technical details, and exploring the advantages and limitations of the formalism.
+
+While I believe that the work is not yet mature enough for IJCAR, I do encourage the authors to continue in this track.
+
+Some minor details:
+- in English, "Bayesian" is written with a capital letter. Change all "bayesian" to "Bayesian"
+- try to avoid contractions. "don't" - "do not", "we've" - "we have", etc.
+- in page 8, "it's" - "its"
+- In Definition 2, to say that both events are inconsistent, it is better to write {u,v}\cap W = \emptyset
+
+
+## REVIEW 3
+
+SUBMISSION: 23
+TITLE: An Algebraic Approach to Stochastic ASP
+AUTHORS: Francisco Coelho, Bruno Dinis and Salvador Abreu
+
+----------- Overall evaluation -----------
+SCORE: -2 (reject)
+----- TEXT:
+The paper presents an approach to add probabilities to answer set programs. In the resulting stochastic answer set programs, rules are combined with stochastic facts, which assign probabilities to program variables. With no rules present, those variables are then treated as independent variables for determining the joint probabilities of different variable assignments. The main question that the paper is concerned with is what to do if also rules are involved, interpreted under the stable model semantics. How to obtain the probability of derived variables, and how are the probabilities of facts affected by the constraints given by the program? Due to the non-monotonic nature of this semantics, this is not straight-forward, and requires a different treatment in monotonic rule languages such as datalog. 
+
+The aim is thus to define a probability measure that assigns probabilities to partial truth assignments (probabilistic events) of variables occurring in the program. As common with probability theories, these partial truth assignments are then called events. Every stable model corresponds to an event, but also subsets and supersets of stable models are events that need a probability assigned. The authors make the reasonable assumption that stable models correspond to disjoint events, and that events that are not compatible to any stable model should have a probability of 0. Based on these assumptions, they then develop a probability measure that takes into account the relation of events to the stable models, as well as the probabilties provided by the stochastic facts. 
+
+After this semantics is introduced, the authors illustrate it on a simple example and a slightly more involved one that is commonly used to illustrate Bayesian networks. The probabilities obtained for the simple example are compared with probabilities that are obtained by a statistical simulation, essentially drawing samples on the probabilistic distribution. The second example showcases how probabilities represented in a Bayesian network could be modelled using their stochatic programs. 
+
+The paper is mostly well-written, and the ideas initially sound convincing. There are some initial issues in the presentation that could be improved (for instance, for self-containment, I think one should at least recall the stable model semantics and its properties, as this is central for the presented method). From page 9 on, I observe some more major issues:
+
+1. I didn't find the argument for Proposition 1 convincing, unless there is something strange in the semantics. Namely, while stable models correspond to pair-wise disjoint events, it should not be the case that all events are disjoint. In particular, if one event
+E1 is a subset of another event E2 (i.e., E1 assigns less values than E2), I would assume that the probability of E2 is contained in that of E1. This is at least how it behaves classically (e.g., without rules). Therefore, the assumption that the total choices cover the entire probability space does not  imply that the probability of all other events, including the stable models, becomes zero. While I would expect that something like Proposition 1 should hold, the present argument needs more work.
+2. For the developed examples, I think it would be insightful to not only provide the probabilities of the classes, but also of the events (e.g.: what is the probability of a? What is the probability of ac?) If this information is supposed to be present in (18), then something is clearly going wrong - how do I interpret the 0 in column "¬a,ac"? What is the event e here?
+3. The "testing of the prior distributions" comes a bit unexpected, and it is not fully clear what is the role. Are you trying to empirically justify your sematics? What is the purpose of doing that in a single example? In any case, the role of this in the greater story of the paper is not clear to me 
+4. Similarly, I don't see why someone would use a stochastic program to model a Bayesian network. If there is a relation, I would rather want to see a general argument, then an illustration on a simple example. In any case, I don't think stochastic answer set programs should be used as replacements of Bayesian networks.
+
+In total, the paper feels somewhat incomplete and incoherent, which is why I do not recommend acceptance.
+
+
@@ -8,15 +8,23 @@
 		},
 		{
 			"path": "../../../prog/contrib/zugzwang"
+		},
+		{
+			"path": "../jupy"
+		},
+		{
+			"path": "../../cv/2024"
 		}
 	],
 	"settings": {
 		"cSpell.words": [
 			"biblatex",
+			"cplint",
 			"CREDAL",
 			"Hirings",
 			"interpretability",
 			"println",
+			"SASP",
 			"stablecore",
 			"testset",
 			"uminus"
@@ -25,6 +33,7 @@
 			"latex"
 		],
 		"aspLanguage.setConfig": "config.json",
-		"julia.environmentPath": "/home/fc/sci/projetos/zugzwang"
+		"julia.environmentPath": "/home/fc/sci/projetos/zugzwang",
+		"liveServer.settings.multiRootWorkspaceName": "zugzwang"
 	}
 }
 \ No newline at end of file
1	1	# Zugzwang Meetings
2	2
	3	+## 2024-03-15 - IJCAR24 Reviews
	4	+
	5	+### Summary
	6	+
	7	+- State-of-the-art:
	8	+ - Thorough comparison with related work
	9	+- Motivation:
	10	+ - Clarify the application of the approach
	11	+ - Explore the advantages and limitations of the formalism
	12	+- Technical details:
	13	+ - Self-containment
	14	+ - Detail syntax and semantics of the considered class of programs.
	15	+ - Clarify the relation of stable models and events
	16	+ - Recall the stable model semantics and its properties
	17	+ - Argument for Proposition 1 [is not] convincing
	18	+- Fixes:
	19	+ - Provide the probabilities of the classes and of the events
	20	+ - Clarify the role of "testing of the prior distributions"
	21	+ - Give a general argument [about Bayesian networks] instead of an illustration on a simple example.
	22	+
	23	+See [Reviews file](text/paper_01/LLNCS/reviews_IJCAR24.md).
	24	+
	25	+
	26	+
	27	+- Para ICLP24
	28	+ - Mais técnico.
	29	+ - Considerar scasp.
	30	+- Para KR24
	31	+ - Mais formal.
	32	+- Overleaf
	33	+ - authentication key: olp_1oPNhAUwN9ihvWzd4n92hEd9UQUbK44ul5Gg
	34	+ - zw-kr: git clone https://git@git.overleaf.com/65f422781f1d04e2c0aefd56
	35	+ - zw-iclp: git clone https://git@git.overleaf.com/65f422dc70a60d8ab7fde402
	36	+
3	37	## 2024-01-30 - Exploratory Research Project
4	38
5	39	> Apply for FCT funding.
6	40
7	41
8		-
9	42	## 2024-01-05 - Next Research Lines
10	43
11	44	> After the base-setting work of "_An Algebraic Approach to Stochastic ASP_" these are the next tasks to consider. Is summary:
...	...	@@ -107,15 +140,15 @@ Scoring programs, as described in our paper, is just a step into **Inductive Log
107	140
108	141	> Target conferences to publish paper "AASASP"
109	142
110		-\| Conference \| Abstract Deadline \| Conference Date \| Location \| OBS \|
111		-\|-----------:\|:------------------\|:----------------\|------------------------------:\|-----------\|
112		-\| IJCAR 2024 \| 2024-01-29 \| 2024-07-3:6 \| Nancy, France \| Picked \|
113		-\| ECAI'24 \| 2024-04-19 \| 2024-10-19:24 \| Santiago de Compostela, Spain \| \|
114		-\| KR 2024 \| 2024-04-24 \| 2024-11-2:8 \| Hanoi, Vietnam \| \|
115		-\| GECCO 24 \| 2024-02-05 \| 2024-07-14:18 \| Melboune, Australia \| \|
116		-\| ICLP 24 \| 2024-04-15 \| \| \| preferred \|
117		-\| JELIA 25 \| \| \| \| \|
118		-\| ICFP 24 \| 2024-03-01 \| 2024-09-2:7 \| Milan, Italy \| \|
	143	+\| Conference \| Abstract Deadline \| Conference Date \| Location \| OBS \|
	144	+\|-----------:\|:------------------\|:----------------\|------------------------------:\|-------------------\|
	145	+\| IJCAR 2024 \| 2024-01-29 \| 2024-07-3:6 \| Nancy, France \| ~Picked~ Rejected \|
	146	+\| ECAI'24 \| 2024-04-19 \| 2024-10-19:24 \| Santiago de Compostela, Spain \| \|
	147	+\| KR 2024 \| 2024-04-24 \| 2024-11-2:8 \| Hanoi, Vietnam \| \|
	148	+\| GECCO 24 \| 2024-02-05 \| 2024-07-14:18 \| Melboune, Australia \| Overdue \|
	149	+\| ICLP 24 \| 2024-04-15 \| \| \| preferred \|
	150	+\| JELIA 25 \| \| \| \| \|
	151	+\| ICFP 24 \| 2024-03-01 \| 2024-09-2:7 \| Milan, Italy \| \|
119	152
120	153	## 2023-02-28 - Looking for Application Examples
121	154
...	...	@@ -173,8 +206,13 @@ What should be the task for the scholarship student? _Use the `Python` API o
173	206	- Get stable models from potassco/s(casp)
174	207	- other?
175	208
176		-
177	209	## 2022-12-05
178	210
179	211	- Created shared folder (gdrive:zugzwang) <https://drive.google.com/drive/folders/1xs-cjxWJzn2JxqeNgh9LX5xWN50BW-Be?usp=share_link>
180		-- Refine project tasks, for Bachelor, M.Sc., Ph.D. students and for researchers.
181	212	\ No newline at end of file
	213	+- Refine project tasks, for Bachelor, M.Sc., Ph.D. students and for researchers.
	214	+
	215	+## Resources
	216	+
	217	+### Conferences
	218	+
	219	+- [Conferences Sheet](https://docs.google.com/spreadsheets/d/1KJdA-zj3Xly-_tSE6tjbd7M9SttC9xBixXoqWZJFVfg/edit#gid=0)
182	220	\ No newline at end of file
...	...
...	...	@@ -0,0 +1,48 @@
	1	+- [x] Dados Gerais
	2	+- [x] Instituições
	3	+ - [x] Instituição proponente
	4	+ - [x] Descrição da Instituição e respectivas competências para o desenvolvimento deste projeto (1500)
	5	+ - [x] Instituições de colaboração (HPCC)
	6	+- [ ] Equipa de Investigação
	7	+ - [x] CV Narrativo do IR
	8	+ - [x] Percurso Científico e Curricular (2000)
	9	+ - [x] Contribuições da originalidade de ideias, ferramentas, metodologias ou conhecimento (2000)
	10	+ - [x] Contribuições para o desenvolvimento de competências ao nível individual e/ou em equipas (3000)
	11	+ - [x] Contribuições para a Comunidade Científica e para a Sociedade (3000)
	12	+ - [x] Resultados ou/e atividades relevantes (2500)
	13	+ - [x] Que relevância atribui a este financiamento para a fase atual da sua carreira e/ou do seu percurso de investigação? (3000)
	14	+ - [ ] Membros (4)
	15	+ - [x] Francisco
	16	+ - [x] Bruno
	17	+ - [x] Salvador
	18	+ - [ ] Miguel confirmar participação
	19	+ - [x] Novas contratações
	20	+ - [x] Consultores
	21	+ - [x] Sinopse dos CV da equipa de investigação (6000)
	22	+ - [x] Francisco
	23	+ - [x] Bruno
	24	+ - [x] Salvador
	25	+ - [x] Miguel
	26	+- [x] Plano de Trabalho
	27	+ - [x] Resumo PT/EN (5000 x2)
	28	+ - [x] Estado da arte (6000)
	29	+ - [x] Plano de investigação e métodos (10000)
	30	+ - [x] Referências bibliográficas (10000)
	31	+ - [x] Publicações Anteriores (5)
	32	+ - [x] FC
	33	+ - [x] BD
	34	+ - [x] SPA
	35	+ - [ ] MA uma/duas publicações nos últimos cinco anos
	36	+ - [x] Tarefas
	37	+ - [x] Lista de milestones
	38	+ - [x] Cronograma
	39	+ - [x] Descrição da estrutura de gestão (3000)
	40	+ - [x] Enquadramento da candidatura nos ODS da Agenda 2030 das Nações Unidas
	41	+ - [x] Fundamentação do enquadramento (3000)
	42	+ - [x] Outros projetos (5 anos)
	43	+- [x] Indicadores
	44	+ - [x] Divulgação (3000)
	45	+- [x] Orçamento
	46	+ - [x] Universidade de Évora
	47	+ - [x] Orçamento global
	48	+ - [x] Plano de financiamento
0	49	\ No newline at end of file
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	1	+
	2	+<!DOCTYPE html>
	3	+<html>
	4	+ <head>
	5	+ <meta http-equiv="X-UA-Compatible" content="IE=edge" />
	6	+ <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
	7	+ <meta name="format-detection" content="telephone=no" />
	8	+ <script type='text/javascript'>window.OutSystemsApp = { basePath: '/Projects/' };</script>
	9	+
	10	+
	11	+ <meta name="viewport" content="viewport-fit=cover, width=device-width, initial-scale=1" />
	12	+<script type="text/javascript">
	13	+(function () {
	14	+ function appendMetaTagAttributes(metaTag, attribute, values) {
	15	+ var elem = document.querySelector("meta[name=" + metaTag + "]");
	16	+
	17	+ if (elem) {
	18	+ var attrContent = elem.getAttribute(attribute);
	19	+ elem.setAttribute(attribute, (attrContent ? attrContent + "," : "") + values.join(","));
	20	+ }
	21	+ }
	22	+
	23	+ if (navigator && /OutSystemsApp/i.test(navigator.userAgent)) {
	24	+ // If this app is running on the native shell, we want to disable the zoom
	25	+ appendMetaTagAttributes("viewport", "content", ["user-scalable=no", "minimum-scale=1.0"]);
	26	+ }
	27	+})();</script>
	28	+
	29	+ <script type="text/javascript" src="scripts/OutSystemsManifestLoader.js?3F3fZzzNKkqKoP2DsjtxFw"></script>
	30	+<script type="text/javascript" src="scripts/OutSystems.js?RnlDcii3Xz75iIHHERIZtA"></script>
	31	+<script type="text/javascript" src="scripts/OutSystemsReactView.js?0bmp5RZ49TZneVNXnO6ymw"></script>
	32	+<script type="text/javascript" src="scripts/cordova.js?7KqI9_oL9hClomz1RdzTqg"></script>
	33	+<script type="text/javascript" src="scripts/NullDebugger.js?pG_2wlzY3NYiuKZRtoLyQQ"></script>
	34	+<script type="text/javascript" src="scripts/Projects.appDefinition.js?PrSt0mgUZuIIDvrGb3OwIg"></script>
	35	+<script type="text/javascript" src="scripts/OutSystemsReactWidgets.js?IdWooa_erXOfwU01FQUTuA"></script>
	36	+<link type="text/css" rel="stylesheet" href="css/_Basic.css?EqGzAe81QbZLXJyfY3oLwA"></link>
	37	+
	38	+ <script type="text/javascript">OSManifestLoader.indexVersionToken = "PpAVEckFK5cEx1aoSbY7vQ";
	39	+</script>
	40	+ </head>
	41	+ <body>
	42	+ <div id="reactContainer"></div>
	43	+ <noscript><span>JavaScript is required</span></noscript>
	44	+
	45	+ <script type="text/javascript" src="scripts/Projects.index.js?_i_B_jY4q5y6aRAMA5bwsQ"></script>
	46	+
	47	+ </body>
	48	+</html>
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	1	+# P04 - Plano de Trabalho
	2	+
	3	+## Resumo
	4	+
	5	+### Resumo em português (5000c)
	6	+
	7	+### Resumo em inglês (5000c)
	8	+
	9	+## Estado da arte e objetivos (6000c)
	10	+
	11	+## Plano de investigação e métodos (10000c)
	12	+
	13	+## Referências bibliográficas (10000c)
	14	+
	15	+> Inclua publicações citadas na descrição técnica e científica da candidatura. Esta lista não está limitada a publicações dos membros da equipa. (APA, MLA, Chicago)
	16	+
	17	+## Publicações anteriores (5 da equipa)
	18	+
	19	+## Tarefas
	20	+
	21	+(externo)
	22	+
	23	+## Calendarização e gestão do projeto
	24	+
	25	+### Lista de milestones
	26	+
	27	+### Cronograma
	28	+
	29	+> Produza uma descrição da calendarização do projeto em formato electrónico. Sugerimos que utilize como ponto de partida a folha de cálculo que disponibilizamos em 2 formatos: (MS Excel) e ([ODF](https://myfct.fct.pt/Projects/ProjectTimelineManagement?ApplicationId=51568#)). Converta a versão final para formato PDF e faça upload, com a designação timeline.pdf.
	30	+
	31	+
	32	+## Questões éticas
	33	+
	34	+## Agenda 2030
	35	+
	36	+> Os Objetivos de Desenvolvimento Sustentável (ODS) e a Agenda 2030, adotados pela quase totalidade dos países do mundo, no contexto das Nações Unidas, definem as prioridades e aspirações do desenvolvimento sustentável global para 2030 e procuram mobilizar esforços globais à volta de um conjunto de objetivos e metas comuns. São 17 ODS, em áreas que afetam a qualidade de vida de todos os cidadãos do mundo e daqueles que ainda estão para vir. [Mais informação sobre os ODS das Nações](https://myfct.fct.pt/Projects/Agenda2030?ApplicationId=51568#).
	37	+
	38	+### Enquadramento da candidatura nos ODS da Agenda 2030 das Nações Unidas
	39	+(uma linha)
	40	+
	41	+### Fundamentação do enquadramento (3000c)
	42	+
	43	+## Outros projetos
	44	+
	45	+> Devem ser listados as candidaturas submetidas ou projetos aprovados (liderados pelo IR) através de avaliação por pares que se tenham iniciado há menos de 5 anos (concluídos ou em curso).
	46	+
	47	+### JuPy
	48	+
	49	+#### Relação com esta candidatura
	50	+- Foi adquirido conhecimento e experiência sobre implementação e execução de programas num sistema distribuído HPC.
	51	+- Foram estabelecidas relações de cooperação técnica e científica entre o PI e a equipa de gestão do cluster "Oblivion \| HPCUE"
	52	+
	53	+- Knowledge and experience was acquired about implementing and executing programs in a distributed HPC system.
	54	+- Technical and scientific cooperation relationships were established between the PI and the management team of the "Oblivion \| HPCUE" cluster.
	55	+
	56	+## Ficheiros anexos
...	...
...	...	@@ -0,0 +1,26 @@
	1	+using Dates
	2	+
	3	+function budget(items, overhead=0.25)
	4	+ partial = sum(items)
	5	+ partial_overhead = overhead * partial
	6	+ total = partial + partial_overhead
	7	+ return (partial, partial_overhead, total)
	8	+end
	9	+
	10	+function get_budget()
	11	+ items = [700, 500, 576, 2660, 12*1686]
	12	+ (partial, overhead, total) = budget(items)
	13	+ println("Partial : $(partial)\nOverhead: $(overhead)\nTotal : $total")
	14	+end
	15	+
	16	+function project_month(n, startdate=Date(2024,09,01))
	17	+ months = Dates.Month(n)
	18	+ return startdate + months
	19	+end
	20	+
	21	+function get_month(month=8)
	22	+ cm = project_month(month)
	23	+ println("M$(month) -> $(cm)")
	24	+end
	25	+
	26	+get_budget()
0	27	\ No newline at end of file
...	...
...	...	@@ -0,0 +1,147 @@
	1	+# Research plan and methods
	2	+
	3	+> In this section, the PI should describe the proposed research plan and the methodologies to be used, focusing on the following questions:
	4	+> - To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
	5	+> - To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
	6	+> - To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
	7	+>
	8	+> Funded projects will now have access to advanced computer resources and research data repositories provided by FCT without the need for further scientific evaluation. This includes computing time in FCT's two new supercomputers, Deucalion and MareNostrum 5. To this end, FCT kindly requests that applicants answer two simple yes/no additional questions:
	9	+> - Identify whether the work plan requires advanced computer resources to be provided by FCT.
	10	+> - Identify whether the work plan requires space in a research data repository to be provided by the FCT.
	11	+
	12	+---
	13	+
	14	+Consider the following state of the art and describe a research plan and the methodologies to be used, focusing on the following questions:
	15	+
	16	+- To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
	17	+
	18	+- To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
	19	+
	20	+- To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
	21	+
	22	+The state of the art is:
	23	+
	24	+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Probabilistic Logic Programming (PLP) is one ongoing effort to address this problem by extending the syntax and semantics of logic programs in order to have them represent and operate probability distributions.
	25	+
	26	+Current systems for PLP, such as ProbLog, P-log, LP^MLN, or cplint, derive a probability distribution from a program. However, for Answer Set Programs (ASP) with probabilistic facts, the characterization of a probability distribution on the program's domain is not straightforward .
	27	+
	28	+In a previous work we address the problem of extending probability from the total choices of an ASP program to its stable models and, from there, to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how SASP can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
	29	+
	30	+This representation of arbitrary bayesian networks conferes to SASP the capability to deal with a very large collection of probability problems and tasks. However, the problem of obtaining such SASP, besides hand-coded, remains open.
	31	+
	32	+In our system some unknowns are represented by numeric parameters that can be estimated later from further information, e.g., evidence. This approach, delaying the assignment of certain parameters, enables later refinement and scoring a partial program from additional evidence.
	33	+
	34	+In turn, scoring of SASP (i.e., models of a probabilistic phenomenon) is a key feature required to the application of evolutionary algorithms. From here we can explore how to induce SASP from BK and evidence.
	35	+
	36	+The calculus of the score of an SASP with respect to evidence was already introduced and illustrated in . It remains to investigate the application of this process to induction of SASP from BK and evidence.
	37	+
	38	+Ideas of this paper have a partial, limited, implementation, available in a public repository.
	39	+
	40	+In the general Induction of Logic Programs (ILP) setting the goal is to algorithmically obtain a (target) logic program. For that, (1) BK (e.g., obtained from experts) is provided in the form of a logic program, describing objects and (first-order) relations of a domain and (2) observations are organized as positive evidence, that should be inferred from the target program, and negative evidence, that should not be inferred from the target program. Moreover, the target program must be (logically) consistent with the BK. ILP is a form of Machine Learning (ML) that offers significant advantages over numeric based ML.
	41	+
	42	+For one, ILP address the problem of Explainable Artificial Intelligence (XAI) because, unlike the large-dimensional vector based models of numeric ML, logic programs are human-readable in the sense that their declarative nature describes what objects are in the domain, their structure, properties and relations.
	43	+Second, ILP describes phenomena with related instances while numeric ML is limited to a single (tabulated) relation where different instances (lines) are independent given the model.
	44	+Third, often a target program is generated from a small set of observations, while, in general, numeric ML models require large datasets to achieve significant accuracy.
	45	+At last, expert knowledge, expressed in the BK, can be utilized to structure the target program, i.e., to model the observations. Again, this is a feature hard to achieve with numeric ML models.
	46	+
	47	+Drawbacks of ILP include the computational complexity of inducing the target program and the general difficulty of logic programs to deal with data with random perturbations. While the later is being addressed by PLP in general and SASP in particular, the computational complexity of induction remains an important challenge that we propose to investigate with this project.
	48	+
	49	+In summary, with this project we aim to continue our exploration on how SASP represent probability distributions, how to use them to model probabilistic phenomena and how they can be induced from BK and evidence.
	50	+
	51	+More specifically, this project's objectives are to investigate:
	52	+
	53	+- The role of program structure and composition in the use of PASP to model probabilistic phenomena.
	54	+- Program transformation rules and space exploration algorithms for SASP.
	55	+- The performance of hand-coded and induced SASP models on selected theoretic and real world cases.
	56	+
	57	+---
	58	+
	59	+### Research Plan and Methodologies
	60	+
	61	+Feasibility and Originality
	62	+
	63	+The outlined scientific approach leverages existing developments in Probabilistic Logic Programming (PLP) and Answer Set Programming (ASP) and extends it with the concept of Stochastic Answer Set Programs (SASP) to represent probability distributions in scenarios where traditional logical representations fall short due to probabilistic phenomena. The novelty lies in the application of algebraic methods to express uncertainty and the integration of evolutionary algorithms for inducing SASP models. Feasibility is supported by previous work demonstrating the representational power of SASP. Originality is derived from the interpretation of PLP and ASP concepts in a novel semantic, and the proposed investigation into program induction from background knowledge and evidence.
	64	+
	65	+Research Methodology
	66	+
	67	+1. Theoretical Analysis: Conduct a thorough analysis of the role of program structure and composition in the utilization of PASP for modeling probabilistic phenomena. This involves investigating how different program structures impact the representation and inference capabilities of SASP.
	68	+
	69	+2. Algorithm Development: Develop program transformation rules and space exploration algorithms tailored for SASP. This includes devising methods to efficiently transform and combine SASP representations and explore the space of possible SASP models.
	70	+
	71	+3. Empirical Evaluation: Evaluate the performance of both hand-coded and induced SASP models on a range of theoretic and real-world cases. This involves designing experiments to assess the accuracy, scalability, and computational efficiency of SASP models in comparison to existing PLP systems.
	72	+
	73	+4. Integration of Evolutionary Algorithms: Investigate the application of evolutionary algorithms for induction of SASP models based on additional background knowledge and evidence. Develop algorithms to update SASP parameters and structure to improve model fit to observed data.
	74	+
	75	+Working Arrangements
	76	+
	77	+- Collaborative Environment: Foster collaboration between researchers with expertise in logic, logic programming, and distributed systems to ensure interdisciplinary perspectives are considered.
	78	+
	79	+- Regular Meetings: Schedule regular meetings (e.g., every three/four months) to discuss progress, address challenges, and align research efforts towards the project objectives.
	80	+
	81	+- Access to Resources: Ensure human and computational resources for theoretical research, algorithm development, experimentation, and data analysis.
	82	+
	83	+Timeline
	84	+
	85	+1. Task Structure and Induction of SASP (SI) (Months 1-12)
	86	+
	87	+ - Theoretical research on program structure and transformation rules conducted by an interdisciplinary team of four members, including the PI.
	88	+ - Identifications of relevant program structure and transformation rules.
	89	+ - Regular meetings and discussions to ensure progress and collaboration within the team.
	90	+ - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
	91	+
	92	+2. Task Integration with existing ASP and ILP software frameworks (INT) (Months 3-15)
	93	+
	94	+ - Implementation, testing, profiling and benchmarking, and documentation conducted by a post-doctoral researcher.
	95	+ - Translation of theoretical findings into practical algorithms and software tools.
	96	+ - Rigorous testing of implemented solutions to ensure correctness and efficiency.
	97	+ - Profiling to identify computation intensive points for improvement.
	98	+ - Benchmarking against existing methods to evaluate performance and identify areas for improvement.
	99	+ - Comprehensive documentation of the developed methodologies, including user guides and technical reports.
	100	+ - Continuous refinement based on feedback from internal testing and validation.
	101	+ - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
	102	+ - Dissemination of outcomes through seminars, and open-source repositories.
	103	+
	104	+3. ask Applications of SASP (APP) (Months 6-18)
	105	+
	106	+ - Application of developed methodologies and software tools to theoretical and real-world problems.
	107	+ - Case studies and experiments conducted to assess the effectiveness and scalability of the proposed approaches.
	108	+ - Analysis of results and comparison with existing state-of-the-art methods.
	109	+ - Publication of research findings in peer-reviewed international journals or presentations at international conferences.
	110	+ - Dissemination of outcomes through seminars, and open-source repositories.
	111	+
	112	+Resources
	113	+
	114	+- Personnel
	115	+
	116	+ - PI: Leads and coordinates all tasks, providing guidance and oversight throughout the project duration.
	117	+ - Interdisciplinary team (4 members, including the PI): Comprising experts in logic, logic programming, and distributed systems, responsible for theoretical research and case exploration.
	118	+ - Post-doctoral researcher: Leads the implementation, testing, benchmarking, and documentation efforts.
	119	+
	120	+- Equipment and Infrastructure
	121	+
	122	+ - High-performance computing resources for conducting complex simulations and experiments.
	123	+ - Software development tools and platforms for coding, testing, and version control.
	124	+ - Access to relevant databases, datasets, and computational libraries for validation and benchmarking.
	125	+
	126	+- Funding
	127	+
	128	+ - Budget allocation for equipment procurement, travel expenses, publication fees, and other project-related costs.
	129	+ - Grant funding to sustain the research and software tools development activities over the designated timeline.
	130	+
	131	+PI Commitment
	132	+
	133	+As the Principal Investigator (PI), I am fully committed to overseeing and ensuring the success of each phase of the research project. My responsibilities include:
	134	+
	135	+- Providing strategic direction and vision for the research activities.
	136	+- Facilitating interdisciplinary collaboration among team members.
	137	+- Securing necessary resources and funding to support the project goals.
	138	+- Monitoring progress and addressing any challenges or setbacks that may arise.
	139	+- Ensuring compliance with ethical guidelines and research protocols.
	140	+- Contributing to the dissemination of research outcomes through publications, presentations, and knowledge sharing initiatives.
	141	+- Mentoring and supporting team members to foster their professional development and growth.
	142	+
	143	+Throughout the project duration, I will maintain open communication channels with all stakeholders, including team members, funding agencies, and collaborators, to ensure transparency and alignment with project objectives. My dedication to the project's success is unwavering, and I am committed to achieving impactful results that advance the field of probabilistic logic programming and inductive logic programming.
	144	+
	145	+Justification
	146	+
	147	+The proposed research methodology aligns with the project's objectives by combining theoretical analysis, algorithm development, empirical evaluation, and interdisciplinary collaboration. The utilization of existing PLP frameworks as a foundation and the integration of evolutionary algorithms introduce innovative elements to address the challenges of data with random perturbations and computational complexity in logic-based probabilistic reasoning. The allocated timelines, resources, and PI's commitment are justified by the ambitious nature of the research objectives and the potential impact of the proposed advancements in probabilistic logic programming.
0	148	\ No newline at end of file
...	...
...	...	@@ -0,0 +1,143 @@
	1	+# Work Plan
	2	+
	3	+## Abstract
	4	+
	5	+> In this section, the summary of the proposal should be presented, in Portuguese and English, with an analysis of the state of the art, the main goals to be addressed, the knowledge and skills available in the group, the strategy and methodologies to be used, identifying the novelty and the expected results.
	6	+>
	7	+> The PI must indicate whether the abstract to be used by the FCT for public disseminating will be the same as the abstract previously filled in. If, for confidentiality reasons, the text of the abstract for publication purposes is different, the PI should click on the button Abstract for publication different. The content of this field will always be the PI's responsibility.
	8	+
	9	+### PT (5000)
	10	+
	11	+### EN (5000)
	12	+
	13	+Analysis of the state of the art
	14	+
	15	+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Here we aim to explore how Answer Set Programs (ASP) with probabilistic facts can lead to characterizations of probability functions on the program's domain, which is not straightforward in the context of ASP (see [1, 2, 3, 4]).
	16	+
	17	+Unlike current systems such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], that derive a probability distribution from a program, in our system some choices are represented by a parameter that can be later estimated from further information, eg observations. This approach enables later refinement and scoring of a partial program of a model from additional evidence.
	18	+
	19	+In [8] we address the problem of extending probability from the total choices of an ASP program to the stable models, and from there to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how ASP with probability annotated facts, formally Stochastic Answer Set Programs (SASP), can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
	20	+
	21	+Main goals to be addressed
	22	+
	23	+Applications of this process include assigning a score to a SASP with respect to the empiric distribution of a given dataset. In turn, this score can be used by evolutionary algorithms searching for optimal models of that dataset.
	24	+
	25	+This makes possible to induce a probabilistic model (a SASP) of observations based and respecting formalized BK. A declarative model of a dataset, expressed in terms of objects and rules of a formal BK, possibly setup from expert knowledge. Such kind of models explain the observations in a (first order) language that, in principle, can be read and interpreted by humans, thus addressing the problem of Explainable Artificial Intelligence (XAI).
	26	+
	27	+Another potential advantage of our approach is that induction of logic programs is usually achieved with small datasets.
	28	+
	29	+Therefore, the driver of this project that frames the tasks, milestones and main objectives is the use of SASP and the study of induction of SASP from BK and observations.
	30	+
	31	+Task "Structure and Induction of SASP (SI)" main goal is a theoretical study for induction of SAPS. It continues the work of [8] by clarifying the role of SASP structure and composition elements (eg stratified or recursive programs, functional symbols) in the stable models, the equivalence relation of events and, from there, proceed to the study of induction of SASP using program space exploration algorithms based on program transformation rules (eg genetic algorithms).
	32	+
	33	+Task "Integration with existing ASP and ILP software frameworks (INT)" main goal is the implementation of software tools to use and induce SASP. This task is expected to benefit from the theoretical research of the previous task and its results to be used, by non-specialist researchers, in future applications.
	34	+
	35	+Task "High Performance Computing for Induction and Use of SASPs (HPC)" main goal is the speed-up and scale-up of use and induction of SASP using distributed HPC systems. It should benefit from the theoretical work of the first task and from some output of the second task. The expected outcome of this task is set of prototype programs and/or libraries exploring complex knowledge bases or large datasets.
	36	+
	37	+Task "Applications of SASPs (APP)" main goal is the application of SASP to theoretical and real-world problems. This task is expected to benefit from the software tools from the second and third tasks. In the end, we should get an assessment of the performance of hand-coded and induced SASPs with respect to selected theoretical and real-world problems.
	38	+
	39	+Knowledge and skills available in the group
	40	+
	41	+Francisco Coelho has a PhD in Computer Science and MSc in Mathematics. His main research work deals with the interplay of statistical and logic AI and he has contributed to/with software supporting research work in the areas of machine learning, agent based simulations and combinatorial game theory.
	42	+
	43	+Bruno Dinis has a PhD in Mathematics. He has written over 20 papers on several aspects of logic, for the most part in proof interpretations and its applications (proof mining).
	44	+
	45	+Salvador Abreu [TODO]
	46	+
	47	+Miguel Avillez [TODO]
	48	+
	49	+Strategy and methodologies to be used
	50	+
	51	+The strategic path
	52	+
	53	+Novelty and the expected results
	54	+
	55	+## State of the art and Objectives (6000)
	56	+
	57	+> In this section, the PI must provide an overview of his/her research field, present the state of the art of the research area in connection with the ground-breaking nature and potential impact of the proposed research project. References to the PI’s previous work should be included. The PI should focus on the following questions:
	58	+> - To what extent does the proposed research address important challenges?
	59	+> - To what extent are the objectives ambitious and beyond the state of the art (e.g. novel concepts and approaches or development between or across disciplines)?
	60	+
	61	+Theoretical state of the art and Objectives
	62	+
	63	+A major limitation of logical representations in real world applications is the implicit assumption that the background knowledge (BK) is perfect. This assumption is problematic if data is noisy, which is often the case. Here we aim to explore how Answer Set Programs (ASP) with probabilistic facts can lead to characterizations of probability functions on the program's domain, which is not straightforward in the context of ASP (see [1, 2, 3, 4]).
	64	+
	65	+Unlike current systems such as ProbLog [5], P-log [3], LP^MLN [6], or cplint [7], that derive a probability distribution from a program, in our system some choices are represented by a parameter that can be later estimated from further information, eg observations. This approach enables later refinement and scoring of a partial program of a model from additional evidence.
	66	+
	67	+In [8] we address the problem of extending probability from the total choices of an ASP program to the stable models, and from there to general events. Our approach is algebraic in the sense that it relies on an equivalence relation over the set of events and uncertainty is expressed with variables and polynomial expressions. In that work we show how ASP with probability annotated facts, formally Stochastic Answer Set Programs (SASP), can represent arbitrary bayesian networks and therefore express any probability distribution of discrete random variables.
	68	+
	69	+While the representation of arbitrary bayesian networks conferes to SASP the capability to represent a very large collection of problems, the problem of obtaining such SASP remains open.
	70	+
	71	+To address it we are intent to utilize the score of an SASP with respect to a dataset (ie evidence), that we introduced and illustrated in [8], to guide evolutionary algorithms exploring a space of programs, thus inducing SASP from evidence and background knowledge.
	72	+
	73	+This is an ambitious objective that we plan to follow with this project by studying (1) the effects of program structure and composition, (2) program transformation rules in task "Structure and Induction of SASP (SI)" and in tasks (3) "Integration with existing ASP and ILP software frameworks (INT)" and (4) "High Performance Computing for Induction and Use of SASP (HPC)". These tasks should provide software tools to use and induce SASP, the former task for general use and the former utilizing distributed HPC to speed-up and scale-up applications of SASP.
	74	+
	75	+Current systems ([3, 5, 6, 7]) adhere to a semantic of probabilistic logic programs different from ours. Therefore, it is necessary to provide a set of software tools to use and induce SASP.
	76	+
	77	+Application state of the art and Objectives
	78	+
	79	+
	80	+## Research plan and methods (10000)
	81	+
	82	+> In this section, the PI should describe the proposed research plan and the methodologies to be used, focusing on the following questions:
	83	+> - To what extent is the outlined scientific approach feasible bearing in mind the originality and/or ground-breaking potential of the proposed research?
	84	+> - To what extent are the proposed research methodology and working arrangements appropriate to achieve the goals of the project?
	85	+> - To what extent are the proposed timelines, resources, and PI´s commitment adequate and properly justified?
	86	+>
	87	+> Funded projects will now have access to advanced computer resources and research data repositories provided by FCT without the need for further scientific evaluation. This includes computing time in FCT's two new supercomputers, Deucalion and MareNostrum 5. To this end, FCT kindly requests that applicants answer two simple yes/no additional questions:
	88	+> - Identify whether the work plan requires advanced computer resources to be provided by FCT.
	89	+> - Identify whether the work plan requires space in a research data repository to be provided by the FCT.
	90	+
	91	+
	92	+## Bibliographic References (1000)
	93	+
	94	+> This section is intended to include the references cited in the state of art and in the research plan and methods, with a cross-referencing methodology chosen by the PI, namely: APA, MLA or Chicago.
	95	+>
	96	+> The following elements are considered for each reference: title; authors' names in the order in which they appear in the publication; name of the book or journal; editorial data, where applicable; volume number; page numbers; year of publication. If the publications are available electronically, you can add their URL, although this is not mandatory.
	97	+>
	98	+> Bibliographical references are not limited to the PI and team members' publications.
	99	+
	100	+1. Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: Semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239.
	101	+2. Verreet, V., Derkinderen, V., Dos Martires, P. Z., & De Raedt, L. (2022, June). Inference and learning with model uncertainty in probabilistic logic programs. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 9, pp. 10060-10069).
	102	+3. Baral, C., Gelfond, M., & Rushton, N. (2009). Probabilistic reasoning with answer sets. Theory and Practice of Logic Programming, 9(1), 57-144.
	103	+4. Pajunen, J., & Janhunen, T. (2021). Solution enumeration by optimality in answer set programming. Theory and Practice of Logic Programming, 21(6), 750-767.
	104	+5. De Raedt, L., Kimmig, A., & Toivonen, H. (2007). ProbLog: A probabilistic Prolog and its application in link discovery. In IJCAI 2007, Proceedings of the 20th international joint conference on artificial intelligence (pp. 2462-2467). IJCAI-INT JOINT CONF ARTIF INTELL.
	105	+6. Lee, J., & Wang, Y. (2016, March). Weighted rules under the stable model semantics. In Fifteenth international conference on the principles of knowledge representation and reasoning.
	106	+7. Alberti, M., Bellodi, E., Cota, G., Riguzzi, F., & Zese, R. (2017). cplint on SWISH: Probabilistic logical inference with a web browser. Intelligenza Artificiale, 11(1), 47-64.
	107	+8. Coelho, F., Dinis, B., & Abreu, S. (2024). An Algebraic Approach to Stochastic ASP. Submitted.
	108	+9. Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
	109	+10. López, J., Múnera, D., Diaz, D., & Abreu, S. (2018). Weaving of metaheuristics with cooperative parallelism. In Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part I 15 (pp. 436-448). Springer International Publishing.
	110	+
	111	+## Past publications (WAITING)
	112	+
	113	+[1] Körner, P., Leuschel, M., Barbosa, J., Costa, V.S., Dahl, V., Hermenegildo, M.V., Morales, J.F., Wielemaker, J., Diaz, D., Abreu, S. and Ciatto, G. (2022). Fifty years of Prolog and beyond. Theory and Practice of Logic Programming, 22(6), 776-858.
	114	+[2] Codognet, Philippe, Daniel Diaz, and Salvador Abreu. "Quantum and Digital Annealing for the Quadratic Assignment Problem." 2022 IEEE International Conference on Quantum Software (QSW). IEEE, 2022.
	115	+[3] Eloy, Eduardo, Vladimir Bushenkov, and Salvador Abreu. "Constraint Modeling for Forest Management." International Conference on Dynamic Control and Optimization. Cham: Springer International Publishing, 2021.
	116	+[4] López, Jheisson, et al. "Weaving of metaheuristics with cooperative parallelism." Parallel Problem Solving from Nature-PPSN XV: 15th International Conference, 2018, Proceedings, Part I 15. Springer International Publishing, 2018.
	117	+[5] Codognet, P., Munera, D., Diaz, D. and Abreu, S., 2018. Parallel local search. Handbook of parallel constraint reasoning, pp.381-417
	118	+
	119	+## Tasks (DONE)
	120	+
	121	+## Project timeline and management
	122	+
	123	+### Timeline (DONE)
	124	+
	125	+### Management (3000)
	126	+
	127	+> in this section, the PI should include a description of the project management structure to be adopted, in particular the coordination between participants, the meetings planned and the reporting structure. The proposed structure will depend on the size of the project and, in particular, the existence of participants from different research units.
	128	+
	129	+## Ethical issues (DONE)
	130	+
	131	+## 2030 Agenda (3000)
	132	+
	133	+> The Sustainable Development Goals (SDGs) and the 2030 Agenda, adopted by almost all countries in the world, in the context of the United Nations, define the priorities and aspirations of global sustainable development for 2030 and seek to mobilize global efforts around a set of common goals and objectives.
	134	+>
	135	+> There are 17 SDGs, in areas that affect the quality of life of all citizens of the world and those who are yet to come.
	136	+>
	137	+> In this section the PI should identify one, or up to a maximum of three, of the 17 Sustainable Development Goals of the United Nations 2030 Agenda and justify how the application fits into the selected SDGs.
	138	+
	139	+
	140	+## Other projects (DONE)
	141	+
	142	+## Attachments (DONE)
	143	+
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	1	+tarfea gestão e coordenação
	2	+tarefa inicial - leavantamento estado arte e ferramentas
	3	+
	4	+tarefa INT -> protótico post-doc
	5	+
	6	+virtual machine migration and server consolidation in datacenters energy, miguel
	7	+
	8	+CV narrativo do IR
	9	+
	10	+Substituir os acrónimos pelos nomes. O avaliador não sabe o que é FCUL, UL, UÉ, etc...
	11	+
	12	+"1997.... About Hilbert's..." devia ser "on Hilbert's...".
	13	+
	14	+O mesmo em 2006.
	15	+
	16	+Remover "2006-2021, Period of minor visible activity... "
	17	+
	18	+Substituir 2008... a 2017 por um único período "2006-2021 - research and teaching activity on... with several publications, e.g., articles and books."
	19	+
	20	+"2021-... Research member of the High Performance Computing Chair (HPC Chair).
	21	+
	22	+"2021-... Preparation and lecturing of training courses on .... under the HPC Chair and the european projects EuroCC and EuroCC2, funded by the European Commission - EuroHPC Joint Undertaking."
	23	+
	24	+2022 PI (Investigador Responsável= of the project REFERENCIA, FCT, Portugal
	25	+
	26	+Contribuições para o desenvolvimento de competências ao nível individual e/ou em equipas
	27	+
	28	+Mudar "teacher" por lecturer or professor
	29	+
	30	+
	31	+Que relevância atribui a este financiamento para a fase atual da sua carreira e/ou do seu percurso de investigação?
	32	+
	33	+By then my unclear research goal become how to combine the strengths of statistical and logic AI.
	34	+
	35	+Esta frase é assassina de ti próprio. Estiveste a dar um tiro no que andaste a fazer.
	36	+
	37	+Other issues interrupted this research.
	38	+
	39	+Hein?
...	...
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	1	+# Research team CV synopsis
	2	+
	3	+- Francisco Coelho completed his PhD in Informatics in 2006 at Universidade de Lisboa under the supervision of Helder Coelho on Artificial Intelligence. Is previous formation is on Mathematics, where he has a Master degree in Mathematics, specialty Algebra, with a dissertation about Hilbert's tenth problem and about geometric computation, advised by Prof. Augusto Franco de Oliveira and Prof. José Félix Costa.
	4	+
	5	+Currently he is Assistant Professor at the Computer Science department of Universidade de Évora, where he has coordinated more than twenty courses and restructured or proposed other six, to the graduation and master degrees. He is supervising three PhD thesis and two MSc dissertations and has supervised other six completed MSc dissertations.
	6	+
	7	+He contributed with software and writing to papers covering a wide range of subjects but mostly about logic and statistical AI. He is integrated member of the Intelligent Systems of the research unit NOVALINCS and member of the scientific team of the High Performance Computing Chair.
	8	+
	9	+- Bruno Dinis completed his PhD in Maths in 2013 at the University of Évora under the supervision of Imme van den Berg on Nonstandard Analysis.
	10	+
	11	+After his doctoral studies, he was a postdoc at the Faculdade de Ciências under the supervision of Fernando Ferreira, working on Proof Theory.
	12	+
	13	+Bruno Dinis is currently an Assistant Professor at the Universidade de Évora. Co-supervised 1 master's dissertation.
	14	+
	15	+He has written over 20 papers on several aspects of logic, for the most part in proof interpretations and its applications (proof mining).
	16	+
	17	+- Salvador Abreu is Full Professor at the University of Évora (UE) School of Science and Technology since 2013, Senior Researcher at NOVA LINCS and President of the Scientific Council at the UE Institute for Research and Advanced Training (IIFA). He currently directs the PhD Program in Informatics at UE.
	18	+
	19	+He holds a Habilitation in Informatics from the University of Évora (2009), a PhD in Informatics from Universidade NOVA de Lisboa (1994), and a BSc in Informatics Engineering from Universidade Nova de Lisboa (1987).
	20	+
	21	+Salvador successfully supervised 9 doctoral theses and is currently directing 3. He was granted an IBM SUR award in 2013 and a JSPS Invitation Fellowship in 2015. He participates or participated as a project member or Principal Investigator in nationally and European funded projects, including OAR, AJACS, STAMPA, JEDI, HORUS, VAPS, BIOECOSYS, AI4EU, EUGREEN and PaCoMoCo.
	22	+
	23	+- Miguel Avillez (PhD in Astrophysics) is a tenured research full professor in Astrophysics at the Institute for Research and Advanced Training, University of Évora, being the Chair-holder of the High Performance Computing Chair. He is a guest professor at the Department of Astronomy and Astrophysics of the Technical University Berlin, Germany. He is the director of the High Performance Computing Centre of the University of Évora that houses the the OBLIVION Supercomputer. His research focuses on theoretical and computational astrophysics, computational atomic physics, and numerical analysis, studying the evolution of the interstellar medium in galaxies, the stars life cycle, the circulation of matter between the disks and galactic halos, and, more recently, the distribution of elements in the first galaxies formed after the Big Bang. In addition he is deeply involved in software development, refactoring and acceleration to take advantage of supercomputing facilities and exascale computing.
	24	+
	25	+His research over the years has been funded by, e.g., the National Science Foundation (US), American Museum of Natural History (US), Compaq (US), Portuguese Science Foundation, European Commission, European Science Foundation, DFG, European Space Agency, and NASA.
	26	+
	27	+Over the years he has been involved in scientific working groups of major international projects, some related to the construction of space telescopes (e.g., WSO-UV, Athena, SIRIUS), and led/leads international consortia in, e.g., computational astrophysics, supercomputing in astrophysical fluid flow, and on HPC & HPDA (2019-2023) and HPC, HPDA & AI (2021-2027). He participated in the PRACE (Partnership for Advanced Computing in Europe; 2011-2021), EuroCC (National Competence Centres in the framework of EuroHPC; 2020-2022). Currently leads the WP6 (High Performance Computing) of the research infrastructure ENGAGE SKA, the Task 19.2 "Training and Awareness" of the NCC Portugal in EuroCC2 (EuroHPC JU) and the WP3 "Training" in the ATTRACT European Digital Innovation Hub, as well, as the ERASMUS+ Advanced Computing Consortium that involves 14 higher education institutions in Portugal. He was the european Benchmark Code Owner of the GADGET software (versions 2 through 4) under PRACE (2017-2021) and is European Training Champion for the projects EuroCC and EuroCC2.
	28	+
	29	+Publishes regularly in top journals in his field and in the Nature journal.
	30	+
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	1	+Subproject commit 199ef143774435c7a0883f2baf6317e8aad60223
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