A new kind of science
Evolving Globally Synchronized Cellular Automata
Proceedings of the 6th International Conference on Genetic Algorithms
IEEE Transactions on Parallel and Distributed Systems
Data mining with cellular automata
ACM SIGKDD Explorations Newsletter
Evolutionary Cellular Automata Based-Approach for Edge Detection
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
A Neuro-Genetic Framework for Pattern Recognition in Complex Systems
Fundamenta Informaticae - Membrane Computing
Training cellular automata for image processing
IEEE Transactions on Image Processing
Learning cellular automata rules for pattern reconstruction task
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
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This paper presents results of the study on application of two-dimensional, three-state cellular automata with von Neumann neighborhood to perform pattern reconstruction task. Searching efficient cellular automata rules is conducted with use of a genetic algorithm. Experiments show a very good performance of discovered rules in solving the reconstruction task despite minimum radius of neighborhood and only partial knowledge about neighborhood states available. The paper also presents interesting reusability possibilities of discovered rules in reconstructing patterns different but similar to ones used during artificial evolution.