Book Volume 4998 2008

Learning Classifier Systems

10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers

ISBN: 978-3-540-88137-7 (Print) 978-3-540-88138-4 (Online)

Table of contents (17 chapters)

  1. Front Matter

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  2. Introduction

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      Chapter

      Pages 1-21

      Learning Classifier Systems: Looking Back and Glimpsing Ahead

  3. Knowledge Representations

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      Chapter

      Pages 22-45

      Analysis of Population Evolution in Classifier Systems Using Symbolic Representations

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      Chapter

      Pages 46-56

      Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets

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      Chapter

      Pages 57-76

      Evolving Fuzzy Rules with UCS: Preliminary Results

  4. Analysis of the System

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      Chapter

      Pages 77-95

      A Principled Foundation for LCS

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      Chapter

      Pages 96-116

      Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS

  5. Mechanisms

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      Chapter

      Pages 117-135

      Analysis and Improvements of the Classifier Error Estimate in XCSF

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      Chapter

      Pages 136-153

      A Learning Classifier System with Mutual-Information-Based Fitness

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      Chapter

      Pages 154-168

      On Lookahead and Latent Learning in Simple LCS

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      Chapter

      Pages 169-188

      A Learning Classifier System Approach to Relational Reinforcement Learning

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      Chapter

      Pages 189-205

      Linkage Learning, Rule Representation, and the χ-Ary Extended Compact Classifier System

  6. New Directions

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      Chapter

      Pages 206-217

      Classifier Conditions Using Gene Expression Programming

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      Chapter

      Pages 218-234

      Evolving Classifiers Ensembles with Heterogeneous Predictors

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      Chapter

      Pages 235-254

      Substructural Surrogates for Learning Decomposable Classification Problems

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      Chapter

      Pages 255-268

      Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System

  7. Applications

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      Chapter

      Pages 269-285

      Technology Extraction of Expert Operator Skills from Process Time Series Data

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      Chapter

      Pages 286-305

      Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks

  8. Back Matter

    Pages -