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Inductive Logic Programming

23rd International Conference, ILP 2013, Rio de Janeiro, Brazil, August 28-30, 2013, Revised Selected Papers

  • Gerson Zaverucha
  • Vítor Santos Costa
  • Aline Paes
Conference proceedings ILP 2013

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8812)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 8812)

Table of contents

  1. Front Matter
    Pages I-XIII
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  2. MetaBayes: Bayesian Meta-Interpretative Learning Using Higher-Order Stochastic Refinement
    Stephen H. Muggleton, Dianhuan Lin, Jianzhong Chen, Alireza Tamaddoni-Nezhad
    Pages 1-17
  3. On Differentially Private Inductive Logic Programming
    Chen Zeng, Eric Lantz, Jeffrey F. Naughton, David Page
    Pages 18-30
  4. Learning Through Hypothesis Refinement Using Answer Set Programming
    Duangtida Athakravi, Domenico Corapi, Krysia Broda, Alessandra Russo
    Pages 31-46
  5. A BDD-Based Algorithm for Learning from Interpretation Transition
    Tony Ribeiro, Katsumi Inoue, Chiaki Sakama
    Pages 47-63
  6. Accelerating Imitation Learning in Relational Domains via Transfer by Initialization
    Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli
    Pages 64-75
  7. A Direct Policy-Search Algorithm for Relational Reinforcement Learning
    Samuel Sarjant, Bernhard Pfahringer, Kurt Driessens, Tony Smith
    Pages 76-92
  8. AND Parallelism for ILP: The APIS System
    Rui Camacho, Ruy Ramos, Nuno A. Fonseca
    Pages 93-106
  9. Generalized Counting for Lifted Variable Elimination
    Nima Taghipour, Jesse Davis, Hendrik Blockeel
    Pages 107-122
  10. A FOIL-Like Method for Learning under Incompleteness and Vagueness
    Francesca A. Lisi, Umberto Straccia
    Pages 123-139
  11. Back Matter
    Pages 141-141
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About these proceedings

Introduction

This book constitutes the thoroughly refereed post-proceedings of the 23rd International Conference on Inductive Logic Programming, ILP 2013, held in Rio de Janeiro, Brazil, in August 2013.
The 9 revised extended papers were carefully reviewed and selected from 42 submissions. The conference now focuses on all aspects of learning in logic, multi-relational learning and data mining, statistical relational learning, graph and tree mining, relational reinforcement learning, and other forms of learning from structured data.

Keywords

Markov decision process algorithms answer set programming artificial intelligence data mining inductive logic programming logic programming logical learning machine learning multi-relational learning probabilistic reasoning relational learning robotics structured data

Editors and affiliations

  • Gerson Zaverucha
    • 1
  • Vítor Santos Costa
    • 2
  • Aline Paes
    • 3
  1. 1.University of Rio de JaneiroRio de JaneiroBrazil
  2. 2.University of PortoPortoPortugal
  3. 3.Fluminense Federal UniversityNiteróiBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-44923-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-44922-6
  • Online ISBN 978-3-662-44923-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site