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Evolving coupled map lattices for computation

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Genetic Programming (EuroGP 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1391))

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Abstract

Genetic programming is used to evolve coupled map lattices for density classification. The most successful evolved rules depending only on nearest neighbors (r = 1) show better performance than existing r = 3 cellular automaton rules on this task.

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Author information

Authors and Affiliations

  1. Institute of Theoretical Physics, Chalmers University of Technology, S-412 96, Göteborg, Sweden

    Claes Andersson & Mats G. Nordahl

  2. Santa Fe Institute, 1399 Hyde Park Road, 87501, Santa Fe, NM, USA

    Mats G. Nordahl

Authors
  1. Claes Andersson
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  2. Mats G. Nordahl
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Editor information

Wolfgang Banzhaf Riccardo Poli Marc Schoenauer Terence C. Fogarty

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© 1998 Springer-Verlag Berlin Heidelberg

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Andersson, C., Nordahl, M.G. (1998). Evolving coupled map lattices for computation. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds) Genetic Programming. EuroGP 1998. Lecture Notes in Computer Science, vol 1391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055935

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  • DOI: https://doi.org/10.1007/BFb0055935

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64360-9

  • Online ISBN: 978-3-540-69758-9

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