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Finding Gliders in Cellular Automata

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Collision-Based Computing

Abstract

Gliders, or localized propagating structures, play a role of autonomous signals in cellular-automata models of collision-based computing devices. A method is described for automatically classifying cellular automata rules for a spectrum of ordered, complex and chaotic dynamics, and thus identify rules that support interacting gliders. This is achieved by a measure of the variance of input-entropy over time. The distribution of rule classes in rule-space is discovered. The method also allows automatic “filtering” of cellular automata space-time patterns to show up gliders and related emergent configurations more clearly. Cellular automata dynamics is shown to exhibit some approximate correlations with global measures on convergence in attractor basins, characterized by the distribution of in-degree sizes in their branching structure, and to the rule parameter Z. The research is based on computer experiments using the software Discrete Dynamics Lab (DDLab) [26]

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Authors
  1. Andrew Wuensche
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Editors and Affiliations

  1. Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, BS16 1QY, UK

    Andrew Adamatzky

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© 2002 Springer-Verlag London

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Wuensche, A. (2002). Finding Gliders in Cellular Automata. In: Adamatzky, A. (eds) Collision-Based Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0129-1_13

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  • DOI: https://doi.org/10.1007/978-1-4471-0129-1_13

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-540-3

  • Online ISBN: 978-1-4471-0129-1

  • eBook Packages: Springer Book Archive

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