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Inductive Logic Programming

32nd International Conference, ILP 2023, Bari, Italy, November 13–15, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Elena Bellodi

    1. Università degli Studi di Ferrara, Ferrara, Italy

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  2. Francesca Alessandra Lisi

    1. Università degli Studi di Bari "Aldo Moro", Bari, Italy

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  3. Riccardo Zese

    1. Università degli Studi di Ferrara, Ferrara, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14363)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ILP 2023.

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About this book

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.

Keywords

Table of contents (12 papers)

  1. Front Matter

    Pages i-xviii
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  2. A Constrained Optimization Approach to Set the Parameters of Probabilistic Answer Set Programs

    • Damiano Azzolini
    Pages 1-15

  3. Regularization in Probabilistic Inductive Logic Programming

    • Elisabetta Gentili, Alice Bizzarri, Damiano Azzolini, Riccardo Zese, Fabrizio Riguzzi
    Pages 16-29Open Access

  4. Towards ILP-Based \(\text {LTL}_\text {f}\) Passive Learning

    • Antonio Ielo, Mark Law, Valeria Fionda, Francesco Ricca, Giuseppe De Giacomo, Alessandra Russo
    Pages 30-45

  5. Learning Strategies of Inductive Logic Programming Using Reinforcement Learning

    • Takeru Isobe, Katsumi Inoue
    Pages 46-61

  6. Select First, Transfer Later: Choosing Proper Datasets for Statistical Relational Transfer Learning

    • Thais Luca, Aline Paes, Gerson Zaverucha
    Pages 62-76

  7. GNN Based Extraction of Minimal Unsatisfiable Subsets

    • Sota Moriyama, Koji Watanabe, Katsumi Inoue
    Pages 77-92

  8. What Do Counterfactuals Say About the World? Reconstructing Probabilistic Logic Programs from Answers to “What If?” Queries

    • Kilian Rückschloß, Felix Weitkämper
    Pages 93-108

  9. Few-Shot Learning of Diagnostic Rules for Neurodegenerative Diseases Using Inductive Logic Programming

    • Dany Varghese, Roman Bauer, Alireza Tamaddoni-Nezhad
    Pages 109-123

  10. An Experimental Overview of Neural-Symbolic Systems

    • Arne Vermeulen, Robin Manhaeve, Giuseppe Marra
    Pages 124-138

  11. Statistical Relational Structure Learning with Scaled Weight Parameters

    • Felix Weitkämper, Dmitriy Ravdin, Ramona Fabry
    Pages 139-153

  12. A Review of Inductive Logic Programming Applications for Robotic Systems

    • Youssef Mahmoud Youssef, Martin E. Müller
    Pages 154-165

  13. Meta-interpretive Learning from Fractal Images

    • Daniel Cyrus, James Trewern, Alireza Tamaddoni-Nezhad
    Pages 166-174

  14. Back Matter

    Pages 175-175
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Other volumes

  1. Inductive Logic Programming

Editors and Affiliations

  • Università degli Studi di Ferrara, Ferrara, Italy

    Elena Bellodi, Riccardo Zese

  • Università degli Studi di Bari "Aldo Moro", Bari, Italy

    Francesca Alessandra Lisi

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