Learning cellular automata rules for pattern reconstruction task

Authors:
Anna Piwonska;Franciszek Seredynski
Affiliations:
Bialystok University of Technology, Computer Science Faculty, Bialystok, Poland;Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland and Polish-Japanese Institute of Information Technology, Warsaw, Poland
Venue:
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Year:
2010

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Abstract

This paper presents results of experiments concerning the scalability of two-dimensional cellular automata rules in pattern reconstruction task. The proposed cellular automata based algorithm runs in two phases: the learning phase and the normal operating phase. The learning phase is conducted with use of a genetic algorithm and its aim is to discover efficient cellular automata rules. A real quality of discovered rules is tested in the normal operating phase. Experiments show a very good performance of discovered rules in solving the reconstruction task.