Synthesis of Desired Binary Cellular Automata Through the Genetic Algorithm
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.
KeywordsGenetic Algorithm Cellular Automaton Block Cipher Coincidence Rate Rule Table
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