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An Evolutionary Approach to the Study of Non-trivial Collective Behavior in Cellular Automata

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Cellular Automata (ACRI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2493))

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Abstract

A genetic algorithm (GA) is used to evolve two and one dimensional cellular automata (CA) to perform a non-trivial collective behavior task. Using as fitness function the average area in the iterative map, the GA is able to discover several rules with the desired behavior. In d = 2 we study the scaling of the attractor versus lattice size and noise. In d = 1, using the tools of the computational mechanics, the structural organization of the CA dynamics is uncovered.

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Authors and Affiliations

  1. Departamento de Física de la Materia Condensada, Universidad de Sevilla, P. Box 1065, 41080, Sevilla, Spain

    Francisco Jiménez-Morales

Authors
  1. Francisco Jiménez-Morales
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Editors and Affiliations

  1. Department of Computer Science, Systems and Communication, University of Milano-Bicocca, Via Bicocca degli Arcimboldi, 8, 20126, Milan, Italy

    Stefania Bandini

  2. Computer Science Department, University of Geneva, 24, Rue du General Dufour, 1211, Geneva 4, Switzerland

    Bastien Chopard

  3. Computer Science Institute Faculty of Sciences, University of Lausanne, 1015, Lausanne, Switzerland

    Marco Tomassini

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© 2002 Springer-Verlag Berlin Heidelberg

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Jiménez-Morales, F. (2002). An Evolutionary Approach to the Study of Non-trivial Collective Behavior in Cellular Automata. In: Bandini, S., Chopard, B., Tomassini, M. (eds) Cellular Automata. ACRI 2002. Lecture Notes in Computer Science, vol 2493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45830-1_4

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  • DOI: https://doi.org/10.1007/3-540-45830-1_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44304-9

  • Online ISBN: 978-3-540-45830-2

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