diff --git a/2024-02-05--biblio.zip b/2024-02-05--biblio.zip
new file mode 100644
index 0000000..fd52aa0
Binary files /dev/null and b/2024-02-05--biblio.zip differ
diff --git a/code/asplang/ASPLang.jl b/code/asplang/ASPLang.jl
index 3c686eb..ad7d6bb 100644
--- a/code/asplang/ASPLang.jl
+++ b/code/asplang/ASPLang.jl
@@ -1,8 +1,8 @@
 module ASPLang
 
-export parse_asp, debug_asp, 
+export parse_asp, debug_asp, pstring,
     literal_grammar, term_grammar, aggregate_grammar, asp_grammar,
-    Node, Variable, StringConstant, SymbolicConstant, AnonymousVariable, NumberConstant, Variable,
+    Node, Terminal, NonTerminal, Variable, StringConstant, SymbolicConstant, AnonymousVariable, NumberConstant, Variable,
     Functor, FunctionTerm,
     Negated, Inverted, Product, Sum,
     LT, LE, EQ, NE, GE, GT,
@@ -13,31 +13,47 @@ export parse_asp, debug_asp,
     Aggregate, Elements, InclusionCondition,
     Constraint, LeftBound, RightBound,
     Choice, RestrictedChoice, Choices,
-    Disjunction, Body, Rule, Restriction, WeakRestriction, Annotation,
+    Disjunction, Head, Body, Rule, Restriction, WeakRestriction, Annotation,
     Query, Program
 
+
+
+abstract type Node end
+Base.:(==)(n1::Node, n2::Node) = (typeof(n1) == typeof(n2)) && (n1.args == n2.args)
+
+pstring(x::Any, level=0) = repr(x)
+abstract type Terminal <: Node end
 macro terminal(lang)
     return quote
-        struct $lang <: Node end
+        struct $lang <: Terminal end
     end
 end
+pstring(x::Terminal, level=0) = "$(" "^level)$(typeof(x))"
 
+abstract type NonTerminal <: Node end
 macro variable(lang)
     return quote
-        struct $lang <: Node
+        struct $lang <: NonTerminal
             args
         end
     end
 end
 
+function pstring(x::NonTerminal, level=0)
+    if typeof(x.args) <: AbstractVector
+        pargs = x.args .|> (z -> pstring(z, level + 2))
+        "\n$(" "^level)$(typeof(x))($(join(pargs, ","))\n$(" "^level))"
+    else
+        pargs = join(pstring.(x.args), ",")
+        "\n$(" "^level)$(typeof(x))($pargs) - $(typeof(x.args))"
+    end
+end
+
 using ParserCombinator
 #=
     DATA STRUCTURES
     =#
 
-abstract type Node end
-Base.:(==)(n1::Node, n2::Node) = (typeof(n1) == typeof(n2)) && (n1.args == n2.args)
-
 @variable Variable
 @variable StringConstant
 @variable SymbolicConstant
@@ -92,6 +108,7 @@ Base.:(==)(n1::Node, n2::Node) = (typeof(n1) == typeof(n2)) && (n1.args == n2.ar
 @variable Disjunction
 @variable Annotation
 @variable Body
+@variable Head
 
 @variable Rule
 @variable Restriction
@@ -316,7 +333,7 @@ statement =
     # strong restriction
     (E":-" + body + E"." > Restriction) |
     # rule
-    (head + Opt(annotation) + Opt(E":-" + body) + E"." |> Rule) |
+    ((head + Opt(annotation) |> Head) + Opt(E":-" + body) + E"." |> Rule) |
     # weak restriction
     (E":~" + Opt(body) + E"." + spc + E"[" + weight_at_level + E"]" |> WeakRestriction)
 statements = StarList(statement, E"")
diff --git a/code/asplang/drafts.jl b/code/asplang/drafts.jl
index 3622b0f..5ca020a 100644
--- a/code/asplang/drafts.jl
+++ b/code/asplang/drafts.jl
@@ -4,8 +4,7 @@ using .ASPLang
 
 function test_parse(source, grammar=asp_grammar)
     expr = parse_asp(source, grammar)
-    println("$source => $(expr).\n")
-    print(pstring(expr))
+    println("$source\n$(pstring(expr))")
 end
 
 # test_parse("\"a\"", term_grammar)
diff --git a/code/asplang/sbf.plp b/code/asplang/sbf.plp
index ffa07cb..71c3522 100644
--- a/code/asplang/sbf.plp
+++ b/code/asplang/sbf.plp
@@ -1,2 +1,3 @@
 a::"0.3".
-b | c :- a.
\ No newline at end of file
+b | c ::"0.7" :- a.
+:- not c.
\ No newline at end of file
diff --git a/pex2024/candidatura.md b/pex2024/candidatura.md
index a64813c..a37c24a 100644
--- a/pex2024/candidatura.md
+++ b/pex2024/candidatura.md
@@ -1,4 +1,102 @@
-# Candidatura PeX - Zugzwang
+# Candidatura PEx - Zugzwang
+
+
+## 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:
+> 1. **Logic Programming** - Stratified & Non-stratified programs
+> 2. **Computer Science** - Inductive Logic Programming
+> 3. **Software** - Integration with Potassco and other frameworks
+> 4. **Applications**
+
+#### Line 1: Logic Programming - Stratified & Non-stratified programs
+
+##### Line 1a - Logic Programs Structure and Properties
+
+> _Stratified_ & _non-stratified_ programs are quoted in the "CREDAL" papers as important classes of logic programs.
+
+Minimal example of a **non-stratified program**.
+
+The following annotated LP, with clauses $c_1, c_2, c_3$ respectively, is non-stratified (because has a cycle with negated arcs) but no head is disjunctive:
+```prolog
+0.3::a.                 % c1
+b :- not c, not a.      % c2
+c :- not b.             % c3
+```
+
+This program has three stable models:
+$$
+\begin{aligned}
+m_1 &= \set{ a, c } \cr
+m_2 &= \set{ \neg a, b } \cr
+m_3 &= \set{ \neg a, c }
+\end{aligned}
+$$
+
+> We should **investigate** _What are stratified programs and why are they important?_ and how does our approach deals with such programs?
+
+##### Line 1b - Investigate the expressiveness of PASP
+
+Consider:
+
+- Recursion
+- Variables,
+- Functional symbols,
+
+##### Line 1c - The equivalence relation
+
+Consider the cases where only $s \subseteq e$ and $e \subseteq s$. Or other refinements. Also consider the inconsistent and independent events.
+
+##### Line 1d - Stability of the error function
+
+Consider alternative error functions. See statistics, Kullback-Leibler divergence
+
+#### Line 2: Computer Science - Inductive Logic Programming
+
+> Proceed from scoring programs to support genetic algorithms or other program space exploration methods.
+
+Scoring programs, as described in our paper, is just a step into **Inductive Logic Programming**. To go further, we need to explore algorithms that:
+
+1. Use **background knowledge**, expressed as a PLP.
+2. Consult **positive examples** that should be _soft_ induced.
+3. Consult **negative examples** that should be _soft_ excluded.
+4. Generate **PLPs** that are scored.
+5. Recombine the **best scored** into a new _population_, using recombination rules.
+
+> In order to do that, **PLPs must be expressed as data structures** to be manipulated. Also **recombination rules** must investigated before become formally expressed and supported with adequate methods.
+
+#### Line 3: Software - Integration with Potassco and other frameworks
+
+> Support annotated programs with zugzwang semantics.
+
+- Bayesian Networks (BII Alice)
+  - Generate an annotated asp program from a bayesian network and run it trough `clingo`.
+  - Recover the stable models from the previous ste and compute the respective probabilities.
+- Program Manipulation
+  - Annotated ASP program _representation_ and a _parser_.
+
+#### Line 4: Applications
+
+> Apply zugzwang to a few showcases, besides the theoretic corner stones (non-stratified, disjunctive, bayes networks), preferably based in real world scenarios, with complex structure and large datasets.
+
+- (Stochastic) Plan Generation
+- Yale-Shooting Problem
+- (Stochastic) Situation Calculus
+- Frame Problem
+- Latent Facts - and core assumptions.
+- Given a **Bayesian Network** (or a **Markov Networks**):
+  - Represent it. (**done** for BNs; MNs?)
+  - Solve the common probability tasks: join (**done**), marginals, conditionals, parameter learning, inferring unobserved variables, sample generation, _etc._
+- Given a _solved_ ASP specification:
+  - What is the marginal probability of the atom `a`? (**done**)
+  - What other probability queries are important to consider?
+- Given an _unsolved_ ASP specification:
+  - What is the probability (distribution?) of the probabilistic fact `a`?
+  - What other questions are relevant? _E.g._ the distribution family of a fact?
+- Given a _solved_ ASP specification and a set of _samples_:
+  - How do the probabilities inferred from the specification match the ones from the empiric distribution? (**done** might see alternative approaches)
+- Given two _solved_ ASP specification and a set of _samples_:
+  - Which specification best describes the empiric distribution? (**done**)
 
 ## Tarefas
 
diff --git a/pex2024/candidatura.pdf b/pex2024/candidatura.pdf
new file mode 100644
index 0000000..19f4609
Binary files /dev/null and b/pex2024/candidatura.pdf differ
diff --git a/projecto-NovaLINCS.gdlink b/projecto-NovaLINCS.gdlink
deleted file mode 100644
index 9650490..0000000
--- a/projecto-NovaLINCS.gdlink
+++ /dev/null
@@ -1 +0,0 @@
-{"url": "https://drive.google.com/file/d/1liS-0PGFXZVVPtfiRZix2JXjXzshbNKw/view?usp=drivesdk", "file_id": "1liS-0PGFXZVVPtfiRZix2JXjXzshbNKw", "account_email": "mangon@gmail.com"}
\ No newline at end of file
--
libgit2 0.21.2