Learning Classifier Systems

by Bacardit, Jaume; Bernado-mansilla, Ester; Butz, Martin V.; Kovacs, Tim; Llora, Xavier

• ISBN13: 9783540881377
• ISBN10: 3540881379
• Format: Paperback
• Copyright: 2008-12-05
• Publisher: Springer-Verlag New York Inc

Summary

This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.

Table of Contents

Introduction
Learning Classifier Systems: Looking Back and Glimpsing Ahead	p. 1
Knowledge Representations
Analysis of Population Evolution in Classifier Systems Using Symbolic Representations	p. 22
Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets	p. 46
Evolving Fuzzy Rules with UCS: Preliminary Results	p. 57
Analysis of the System
A Principled Foundation for LCS	p. 77
Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS	p. 96
Mechanisms
Analysis and Improvements of the Classifier Error Estimate in XCSF	p. 117
A Learning Classifier System with Mutual-Information-Based Fitness	p. 136
On Lookahead and Latent Learning in Simple LCS	p. 154
A Learning Classifier System Approach to Relational Reinforcement Learning	p. 169
Linkage Learning, Rule Representation, and the X-Ary Extended Compact Classifier System	p. 189
New Directions
Classifier Conditions Using Gene Expression Programming (Invited Paper)	p. 206
Evolving Classifiers Ensembles with Heterogeneous Predictors	p. 218
Substructural Surrogates for Learning Decomposable Classification Problems	p. 235
Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System	p. 255
Applications
Technology Extraction of Expert Operator Skills from Process Time Series Data	p. 269
Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks	p. 286
Author Index	p. 307
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