- Declarative Sequential Pattern Mining in ASP
- Extracting Rules from ML models in Angluin⁰́₉s 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 ⁰́₋What if?⁰́₊ 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 13⁰́₃15, 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.