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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Suzuki, S., Saito, T. (2006). Synthesis of Desired Binary Cellular Automata Through the Genetic Algorithm. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_81
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DOI: https://doi.org/10.1007/11893295_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46484-6
Online ISBN: 978-3-540-46485-3
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