Evolutionary Learning and Stability of Mixed-Rule Cellular Automata

  • Ryo Sawayama
  • Toshimichi Saito
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8835)


This paper studies the cellular automaton (CA) governed by combination of two rules. First, we analyze a class of CA that generates several isolated spatiotemporal patterns without transient phenomena. Second, we present an evolutionary algorithm that tries to optimize the combination of two rules to stabilize the desired isolated patterns. Performing basic numerical experiments, it is shown that the evolutionary algorithm can make transient phenomena and can stabilize the desired isolated patterns.


cellular automaton genetic algorithm stability 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ryo Sawayama
    • 1
  • Toshimichi Saito
    • 1
  1. 1.Hosei UniversityKoganeiJapan

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