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

    Pages -

  2. Introduction

    1. No Access

      Book Chapter

      Pages 1-21

      Learning Classifier Systems: Looking Back and Glimpsing Ahead

  3. Knowledge Representations

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      Book Chapter

      Pages 22-45

      Analysis of Population Evolution in Classifier Systems Using Symbolic Representations

    2. No Access

      Book Chapter

      Pages 46-56

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

    3. No Access

      Book Chapter

      Pages 57-76

      Evolving Fuzzy Rules with UCS: Preliminary Results

  4. Analysis of the System

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      Book Chapter

      Pages 77-95

      A Principled Foundation for LCS

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      Book Chapter

      Pages 96-116

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

  5. Mechanisms

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      Book Chapter

      Pages 117-135

      Analysis and Improvements of the Classifier Error Estimate in XCSF

    2. No Access

      Book Chapter

      Pages 136-153

      A Learning Classifier System with Mutual-Information-Based Fitness

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      Book Chapter

      Pages 154-168

      On Lookahead and Latent Learning in Simple LCS

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      Book Chapter

      Pages 169-188

      A Learning Classifier System Approach to Relational Reinforcement Learning

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      Book Chapter

      Pages 189-205

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

  6. New Directions

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      Book Chapter

      Pages 206-217

      Classifier Conditions Using Gene Expression Programming

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      Book Chapter

      Pages 218-234

      Evolving Classifiers Ensembles with Heterogeneous Predictors

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      Book Chapter

      Pages 235-254

      Substructural Surrogates for Learning Decomposable Classification Problems

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      Book Chapter

      Pages 255-268

      Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System

  7. Applications

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      Book Chapter

      Pages 269-285

      Technology Extraction of Expert Operator Skills from Process Time Series Data

    2. No Access

      Book Chapter

      Pages 286-305

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

  8. Back Matter

    Pages -