Inductive Logic Programming: 13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003. Proceedings

✍ Scribed by Ross D. King (auth.), Tamás Horváth, Akihiro Yamamoto (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2003
• Tongue: English
• Leaves: 415
• Series: Lecture Notes in Computer Science 2835 : Lecture Notes in Artificial Intelligence
• Edition: 1
• Category: Library

✦ Synopsis

This book constitutes the refereed proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003, held in Szeged, Hungary in September/October 2003.

The 23 revised full papers presented were carefully reviewed and selected from 53 submissions. Among the topics addressed are multirelational data mining, complexity issues, theory revision, clustering, mathematical discovery, relational reinforcement learning, multirelational learning, inductive inference, description logics, grammar systems, and inductive learning.

✦ Table of Contents

Front Matter....Pages -
A Personal View of How Best to Apply ILP....Pages 1-1
Agents that Reason and Learn....Pages 2-3
Mining Model Trees: A Multi-relational Approach....Pages 4-21
Complexity Parameters for First-Order Classes....Pages 22-37
A Multi-relational Decision Tree Learning Algorithm – Implementation and Experiments....Pages 38-56
Applying Theory Revision to the Design of Distributed Databases....Pages 57-74
Disjunctive Learning with a Soft-Clustering Method....Pages 75-92
ILP for Mathematical Discovery....Pages 93-111
An Exhaustive Matching Procedure for the Improvement of Learning Efficiency....Pages 112-129
Efficient Data Structures for Inductive Logic Programming....Pages 130-145
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning....Pages 146-163
On Condensation of a Clause....Pages 164-179
A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting....Pages 180-196
Comparative Evaluation of Approaches to Propositionalization....Pages 197-214
Ideal Refinement of Descriptions in $\mathcal{AL}$ -Log....Pages 215-232
Which First-Order Logic Clauses Can Be Learned Using Genetic Algorithms?....Pages 233-250
Improved Distances for Structured Data....Pages 251-268
Induction of Enzyme Classes from Biological Databases....Pages 269-280
Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars....Pages 281-298
Induction of the Effects of Actions by Monotonic Methods....Pages 299-310
Hybrid Abductive Inductive Learning: A Generalisation of Progol....Pages 311-328
Query Optimization in Inductive Logic Programming by Reordering Literals....Pages 329-346
Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data....Pages 347-364
Relational IBL in Music with a New Structural Similarity Measure....Pages 365-382
An Effective Grammar-Based Compression Algorithm for Tree Structured Data....Pages 383-400
Back Matter....Pages -

✦ Subjects

Artificial Intelligence (incl. Robotics); Computer Science, general; Programming Techniques; Mathematical Logic and Formal Languages