Evolutionary design of rule changing cellular automata

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.