Abstract
The difficulty of designing cellular automatons’ transition rules to perform a particular problem has severely limited their applications. In this paper we propose a new programming method of cellular computers using genetic algorithms. We consider a pair of rules and the number of rule iterations as a step in the computer program. The present method is meant to reduce the complexity of a given problem by dividing the problem into smaller ones and assigning a distinct rule to each. Experimental results using density classification and synchronization problems prove that our method is more efficient than a conventional one.
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Kanoh, H., Wu, Y. (2003). Evolutionary Design of Rule Changing Cellular Automata. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_37
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DOI: https://doi.org/10.1007/978-3-540-45224-9_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40803-1
Online ISBN: 978-3-540-45224-9
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