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.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
35
5 s/w Abbildungen, 35 farbige Abbildungen
XVIII, 175 p. 40 illus., 35 illus. in color.
ISBN-13
978-3-031-49299-0 (9783031492990)
DOI
10.1007/978-3-031-49299-0
Schweitzer Klassifikation
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.
