3e0f9b8a
 Francisco Coelho
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# Probabilistic ILP
**Check** Conformal prediction.
> Fonte: [Turning 30: New Ideas in Inductive Logic Programming](https://arxiv.org/abs/2002.11002)
## Introduction
- How pILP relates to:
- ILP?
- ASP?
- RML?
- What
- tools?
- methods?
- theory?
- Distributed semantics
- applications?
### Overview of Bibliography and State of the Art
Recursion; Predicate Invention; Higher order, ASP Hypotheses; Optimality; Prolog, ASP, NNs
## Context
### Kanren
### Inductive Logic Programming
### Answer Set Programming
### Relational Machine Learning
### SAT Solvers
## Tools
- [(mini)kanren](http://minikanren.org/)
- in Julia: [MuKanren](https://github.com/latticetower/MuKanren.jl), [YA microkanren in Julia](https://www.philipzucker.com/yet-another-microkanren-in-julia/)!.
- [metagol | archive](https://github.com/metagol/metagol) _superseeded by **popper**._
- ILP: [popper](https://github.com/logic-and-learning-lab/Popper)
- ASP: [ILASP](https://github.com/ilaspltd/ILASP-releases)
- [Inspire | Kazmi et al. 2017]()
- ASP: [Potassco: clingo, clasp, ...](https://potassco.org/)
- [cplint (on SWISH)](http://cplint.ml.unife.it/)
- exact probabilistic inference (PITA)
- Fabrizio Riguzzi and Terrance Swift. Well-definedness and efficient inference for probabilistic logic programming under the distribution semantics. Theory and Practice of Logic Programming, 13(Special Issue 02 - 25th Annual GULP Conference):279-302, © Cambridge University Press, March 2013.
- Monte Carlo inference (MCINTYRE)
- Fabrizio Riguzzi. MCINTYRE: A Monte Carlo system for probabilistic logic programming. Fundamenta Informaticae, 124(4):521-541, © IOS Press, 2013.
- Metropolis/Hastings sampling
- Arun Nampally and C. R. Ramakrishnan. Adaptive MCMC-Based Inference in Probabilistic Logic Programs. arXiv preprint arXiv:1403.6036, 2014.
- parameter learning (EMBLEM)
- Elena Bellodi and Fabrizio Riguzzi. Expectation Maximization over binary decision diagrams for probabilistic logic programs. Intelligent Data Analysis, 17(2):343-363, © IOS Press, 2013.
- SLIPCOVER algorithm for structure learning
- Elena Bellodi and Fabrizio Riguzzi. Structure learning of probabilistic logic programs by searching the clause space. Theory and Practice of Logic Programming, 15(2):169-212, © Cambridge University Press, 2015.
- LEMUR algorithm for structure learning
- Nicola Di Mauro, Elena Bellodi, and Fabrizio Riguzzi. Bandit-based Monte-Carlo structure learning of probabilistic logic programs. Machine Learning, 100(1):127-156, © Springer International Publishing, July 2015.
## Methods
## Theory
### Distributed Semantics
## Applications
### ELearning
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