Inductive Logic Programming

1. Front Matter

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2. Invited Talks

   1. Inference and Learning in Planning

      • Hector Geffner

      Pages 1-1

   2. Beyond Reward: The Problem of Knowledge and Data

      • Richard S. Sutton

      Pages 2-6

   3. Exploiting Constraints

      • Toby Walsh

      Pages 7-13

3. Special Issue Extended Abstracts

   1. Online Bayesian Inference for the Parameters of PRISM Programs

      • James Cussens

      Pages 14-19

   2. Learning Compact Markov Logic Networks with Decision Trees

      • Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao

      Pages 20-25

   3. Relational Networks of Conditional Preferences

      • Frédéric Koriche

      Pages 26-32

   4. k-Optimal: A Novel Approximate Inference Algorithm for ProbLog

      • Joris Renkens, Guy Van den Broeck, Siegfried Nijssen

      Pages 33-38

   5. Learning Directed Relational Models with Recursive Dependencies

      • Oliver Schulte, Hassan Khosravi, Tong Man

      Pages 39-44

4. Research Papers

   1. Integrating Model Checking and Inductive Logic Programming

      • Dalal Alrajeh, Alessandra Russo, Sebastian Uchitel, Jeff Kramer

      Pages 45-60

   2. Learning the Structure of Probabilistic Logic Programs

      • Elena Bellodi, Fabrizio Riguzzi

      Pages 61-75

   3. Subgroup Discovery Using Bump Hunting on Multi-relational Histograms

      • Radomír Černoch, Filip Železný

      Pages 76-90

   4. Inductive Logic Programming in Answer Set Programming

      • Domenico Corapi, Alessandra Russo, Emil Lupu

      Pages 91-97

   5. Graph-Based Relational Learning with a Polynomial Time Projection Algorithm

      • Brahim Douar, Michel Liquiere, Chiraz Latiri, Yahya Slimani

      Pages 98-112

   6. Interleaved Inductive-Abductive Reasoning for Learning Complex Event Models

      • Krishna Dubba, Mehul Bhatt, Frank Dylla, David C. Hogg, Anthony G. Cohn

      Pages 113-129

   7. Predictive Sequence Miner in ILP Learning

      • Carlos Abreu Ferreira, João Gama, Vítor Santos Costa

      Pages 130-144

   8. Conceptual Clustering of Multi-Relational Data

      • Nuno A. Fonseca, Vítor Santos Costa, Rui Camacho

      Pages 145-159

   9. Expressive Power of Safe First-Order Logical Decision Trees

      • Joris J. M. Gillis, Jan Van den Bussche

      Pages 160-172

   10. DNF Hypotheses in Explanatory Induction

       • Katsumi Inoue

       Pages 173-188

   11. Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs

       • Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato

       Pages 189-203

This book constitutes the thoroughly refereed post-proceedings of the 21st International Conference on Inductive Logic Programming, ILP 2011, held in Windsor Great Park, UK, in July/August 2011. The 24 revised full papers were carefully reviewed and selected from 66 submissions. Also included are five extended abstracts and three invited talks. The papers represent the diversity and vitality in present ILP research including ILP theory, implementations, probabilistic ILP, biological applications, sub-group discovery, grammatical inference, relational kernels, learning of Petri nets, spatial learning, graph-based learning, and learning of action models.

• artificial intelligence
• graphs
• machine learning
• probabilistic models
• relational networks

• Department of Computer Science, Imperial College London, London, UK

  Stephen H. Muggleton, Alireza Tamaddoni-Nezhad

• Dipartimento di Informatica, Università degli Studi di Bari “Aldo Moro”, Bari, Italy

  Francesca A. Lisi

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