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Synthesis of Desired Binary Cellular Automata Through the Genetic Algorithm

  • Satoshi Suzuki
  • Toshimichi Saito
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)

Abstract

This paper presents a GA-based synthesis algorithm of a cellular automaton ( CA ) that can generate a desired spatio-temporal pattern. Time evolution of CA is determined by a rule table the number of which is enormous even for relatively small size CAs: the brute-force search is almost impossible. In our GA-based synthesis algorithm, a gene corresponds to a rule and a masking technique is used to preserve gene(s) with good fitness. Performing basic numerical experiments we have confirmed that the masking works effectively and the algorithm can generate a desired rule table. We have also considered an application to reduction of noise inserted randomly to a spatio-temporal pattern.

Keywords

Genetic Algorithm Cellular Automaton Block Cipher Coincidence Rate Rule Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Satoshi Suzuki
    • 1
  • Toshimichi Saito
    • 1
  1. 1.Hosei UniversityKoganeiJapan

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