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International Workshop on Learning Classifier Systems

International Workshop on Learning Classifier Systems

IWLCS 2009, IWLCS 2008: Learning Classifier Systems pp 38–46Cite as

Coevolution of Pattern Generators and Recognizers

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6471))

Abstract

Proposed is an automatic system for creating pattern generators and recognizers that may provide new and human-independent insight into the pattern recognition problem. The system is based on a three-cornered coevolution of image-transformation programs.

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Author information

Authors and Affiliations

  1. Prediction Dynamics, Concord, MA, 01742, USA

    Stewart W. Wilson

  2. Department of Industrial and Enterprise Systems Engineering, The University of Illinois at Urbana-Champaign, IL, 61801, USA

    Stewart W. Wilson

Authors
  1. Stewart W. Wilson
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Editor information

Editors and Affiliations

  1. School of Computer Science, ASAP research group, University of Nottingham, Jubilee Campus, Nottingham, NG8 1BB, and Multidisciplinary Centre for Integrative Biology, School of Biosciences, LE12 5RD, Sutton Bonington, UK

    Jaume Bacardit

  2. School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, 6140, Wellington, New Zealand

    Will Browne

  3. Department of Brain and Cognitive Sciences, University of Rochester, Meliora Hall, 14627, Rochester, NY, USA

    Jan Drugowitsch

  4. Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins, 2, 08022, Barcelona, Spain

    Ester Bernadó-Mansilla

  5. Department of Psychology III, University of Würzburg, COBOSLAB – Cognitive Bodyspaces: Learning and Behavior,, Röntgenring 11, 97070, Würzburg, Germany

    Martin V. Butz

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Wilson, S.W. (2010). Coevolution of Pattern Generators and Recognizers. In: Bacardit, J., Browne, W., Drugowitsch, J., Bernadó-Mansilla, E., Butz, M.V. (eds) Learning Classifier Systems. IWLCS IWLCS 2009 2008. Lecture Notes in Computer Science(), vol 6471. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17508-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-17508-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17507-7

  • Online ISBN: 978-3-642-17508-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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