Identifying Cellular Automata Rules

Ken-ichi Maeda and Chiaki Sakama

Journal of Cellular Automata, vol.2(1), pages 1-20, 2007.

Abstract

This paper studies a method for identifying cellular automata rules (CA rules). Given a sequence of CA configurations, we first seek an appropriate neighborhood of a cell and collect cellular changes of states as evidences. The collected evidences are then classified using a decision tree, which is used for constructing CA transition rules. Conditions for classifying evidences in a decision tree are computed using genetic programming. We perform experiments using several types of CAs and verify that the proposed method successfully identifies correct CA rules.

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