An inductive logic programming system

Metagol - an inductive logic programming system

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

cplint is a suite of programs for reasoning with probabilistic logic programs

Symbolic Reinforcement Learning using Inductive Logic Programming

(Explainable AI) - Learning Non-Monotonic Logic Programs From Statistical Models Using High-Utility Itemset Mining

Code for the papers "Induction of Subgoal Automata for Reinforcement Learning" (AAAI-20) and "Induction and Exploitation of Subgoal Automata for Reinforcement Learning" (JAIR).

Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform human-designed algorithms

Top-down induction of first-order logical decision trees: master AI thesis implementation

A largely incomplete but hopefully useful list of links to datasets for relational learning and inductive logic programming. No guarantees on availability.

Python package for fetching and using srlearn-compatible relational datasets.

bddem is a SWI-Prolog pack for using Binary Decision Diagrams

A novel Inductive Logic Programming(ILP) system based on Meta Inverse Entailment in Python.

Symbolic function approximator aims to generate a function using a genetic algorithm to approximate a data distribution using the symbolic paradigm with programming logic.

C. Hocquette, A. Niskanen, R. Morel, M. Järvisalo, and A. Cropper, Learning big logical rules by joining small rules, IJCAI, 2024.

C. Hocquette and A. Cropper, Learning programs with magic values.

A code base for Automated Relational Feature Engineering

C. Hocquette, A. Niskanen, M Järvisalo, and Andrew Cropper, Learning MDL Logic Programs From Noisy Data, AAAI24.

This repo contains my undergraduate thesis work where I tried to combine ILP with MaxEnt.

BotGNN: Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment