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

Author:   Jaume Bacardit ,  Ester Bernadó-Mansilla ,  Martin V. Butz ,  Tim Kovacs
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2008 ed.
Volume:   4998
ISBN:  

9783540881377


Pages:   307
Publication Date:   23 October 2008
Format:   Paperback
Availability:   In Print   Availability explained
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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


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Author:   Jaume Bacardit ,  Ester Bernadó-Mansilla ,  Martin V. Butz ,  Tim Kovacs
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2008 ed.
Volume:   4998
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   0.492kg
ISBN:  

9783540881377


ISBN 10:   3540881379
Pages:   307
Publication Date:   23 October 2008
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Learning Classifier Systems: Looking Back and Glimpsing Ahead.- Knowledge Representations.- Analysis of Population Evolution in Classifier Systems Using Symbolic Representations.- Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets.- Evolving Fuzzy Rules with UCS: Preliminary Results.- Analysis of the System.- A Principled Foundation for LCS.- Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS.- Mechanisms.- Analysis and Improvements of the Classifier Error Estimate in XCSF.- A Learning Classifier System with Mutual-Information-Based Fitness.- On Lookahead and Latent Learning in Simple LCS.- A Learning Classifier System Approach to Relational Reinforcement Learning.- Linkage Learning, Rule Representation, and the ?-Ary Extended Compact Classifier System.- New Directions.- Classifier Conditions Using Gene Expression Programming.- Evolving Classifiers Ensembles with Heterogeneous Predictors.- Substructural Surrogates for Learning Decomposable Classification Problems.- Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System.- Applications.- Technology Extraction of Expert Operator Skills from Process Time Series Data.- Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks.

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