Inductive Logic Programming  32nd International Conference, ILP 2023, Bari, Italy, November 13-15, 2023, Proceedings /  [electronic resource] : 
edited by Elena Bellodi, Francesca Alessandra Lisi, Riccardo Zese. 
 - 1st ed. 2023. 
 - XVIII, 175 p. 40 illus., 35 illus. in color.  online resource. 
 - Lecture Notes in Artificial Intelligence,  14363  2945-9141 ; .
 - Lecture Notes in Artificial Intelligence,  14363 .
<br/><br/>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. 
<br/><br/> 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. 
<br/><br/><label>ISBN: </label>9783031492990 
<br/><br/><label>Standard No.: </label>10.1007/978-3-031-49299-0  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Artificial intelligence.<br/>Computer engineering.<br/>Computer networks .<br/>Compilers (Computer programs).<br/>Computer science.<br/>Machine theory.<br/>Artificial Intelligence.<br/>Computer Engineering and Networks.<br/>Compilers and Interpreters.<br/>Computer Science Logic and Foundations of Programming.<br/>Formal Languages and Automata Theory.
<br/><br/><label>LC Class. No.: </label>Q334-342 TA347.A78 
<br/><br/><label>Dewey Class. No.: </label>006.3