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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Learning Cellular Automata Rules for Pattern Reconstruction Task
verfasst von : Anna Piwonska, Franciszek Seredynski
Erschienen in: Simulated Evolution and Learning
Verlag: Springer Berlin Heidelberg
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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.