Inductive Logic Programming [electronic resource] : 32nd International Conference, ILP 2023, Bari, Italy, November 13-15, 2023, Proceedings / edited by Elena Bellodi, Francesca Alessandra Lisi, Riccardo Zese.

Declarative Sequential Pattern Mining in ASP -- Extracting Rules from ML models in Angluin's Style -- A Constrained Optimization Approach to Set the Parameters of Probabilistic Answer Set Programs -- Regularization in Probabilistic Inductive Logic Programming -- Towards ILP-based LTLf passive learning -- Learning Strategies of Inductive Logic Programming Using Reinforcement Learning -- Select first, transfer later: choosing proper datasets for statistical relational transfer learning -- GNN based Extraction of Minimal Unsatisfiable Subsets -- What Do Counterfactuals Say about the World? Reconstructing Probabilistic Logic Programs from Answers to "What if?" Queries -- Few-shot learning of diagnostic rules for neurodegenerative diseases using Inductive Logic Programming -- An Experimental Overview of Neural-Symbolic Systems -- Statistical relational structure learning with scaled weight parameters -- A Review of Inductive Logic Programming Applications for Robotic Systems -- Meta Interpretive Learning from Fractal images.

This book constitutes the refereed proceedings of the 32nd International Conference on Inductive Logic Programming, ILP 2023, held in Bari, Italy, during November 13-15, 2023. The 11 full papers and 1 short paper included in this book were carefully reviewed and selected from 18 submissions. They cover all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.