Learning Classifier Systems

1. Front Matter

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2. LCS and Related Methods

   1. Speeding Up Matching in Learning Classifier Systems Using CUDA

      • Pier Luca Lanzi, Daniele Loiacono

      Pages 1-20

   2. Evolution of Interesting Association Rules Online with Learning Classifier Systems

      • Albert Orriols-Puig, Jorge Casillas

      Pages 21-37

   3. Coevolution of Pattern Generators and Recognizers

      • Stewart W. Wilson

      Pages 38-46

3. Function Approximation

   1. How Fitness Estimates Interact with Reproduction Rates: Towards Variable Offspring Set Sizes in XCSF

      • Patrick O. Stalph, Martin V. Butz

      Pages 47-56

   2. Current XCSF Capabilities and Challenges

      • Patrick O. Stalph, Martin V. Butz

      Pages 57-69

4. LCS in Complex Domains

   1. Recursive Least Squares and Quadratic Prediction in Continuous Multistep Problems

      • Daniele Loiacono, Pier Luca Lanzi

      Pages 70-86

   2. Use of a Connection-Selection Scheme in Neural XCSF

      • Gerard David Howard, Larry Bull, Pier-Luca Lanzi

      Pages 87-106

   3. Building Accurate Strategies in Non Markovian Environments without Memory

      • Énée Gilles, Péroumalnaïk Mathias

      Pages 107-126

   4. Classification Potential vs. Classification Accuracy: A Comprehensive Study of Evolutionary Algorithms with Biomedical Datasets

      • Ajay Kumar Tanwani, Muddassar Farooq

      Pages 127-144

5. Applications

   1. Supply Chain Management Sales Using XCSR

      • María Franco, Ivette Martínez, Celso Gorrin

      Pages 145-165

   2. Identifying Trade Entry and Exit Timing Using Mathematical Technical Indicators in XCS

      • Richard Preen

      Pages 166-184

   3. On the Homogenization of Data from Two Laboratories Using Genetic Programming

      • Jose G. Moreno-Torres, Xavier Llorà, David E. Goldberg, Rohit Bhargava

      Pages 185-197

6. Back Matter

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This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Atlanta, GA, USA in July 2008, and in Montreal, Canada, in July 2009 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO. The 12 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on LCS in general, function approximation, LCS in complex domains, and applications.

• APCS
• LCS
• LWPR
• XCS
• XCSF
• algorithmic learning
• approximation
• biomedical datasets
• classification
• classifier systems
• complexity
• data mining
• evolutionary rules
• fuzzy rules
• fuzzy sets
• knowledge discovery
• knowledge representation
• learning classifier systems
• multistep problems
• optimization

• School of Computer Science, ASAP research group, University of Nottingham, Jubilee Campus, Nottingham, NG8 1BB, and Multidisciplinary Centre for Integrative Biology, School of Biosciences, Sutton Bonington, UK

  Jaume Bacardit

• School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand

  Will Browne

• Department of Brain and Cognitive Sciences, University of Rochester, Rochester, USA

  Jan Drugowitsch

• Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Barcelona, Spain

  Ester Bernadó-Mansilla

• Department of Psychology III, University of Würzburg, COBOSLAB – Cognitive Bodyspaces: Learning and Behavior,, Würzburg, Germany

  Martin V. Butz

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