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Evolution of non-uniform cellular automata using a genetic algorithm: diversity and computation

Published:07 July 2007Publication History

ABSTRACT

We used a genetic algorithm to evaluate the cost / benefit of diversity in evolving sets of rules for non-uniform cellular automata solving the density classification problem.

References

  1. Gacs, P., Kurdyumov, G. L., and Levin, L. A. One dimensional uniform arrays that wash out finite islands. Problemy Peredachi Informatsii 14 (1978), 92--98.Google ScholarGoogle Scholar
  2. Mitchell, M., Crutchfield, J. P., and Das, R. Evolving cellular automata with genetic algorithms: A review of recent work. In Proceedings of the First International Conference on Evolutionary Computation and Its Applications (Moscow, Russia, 1996), Russian Academy of Sciences.Google ScholarGoogle Scholar
  3. Sipper, M. Evolution of Parallel Cellular Machines: The Cellular Programming Approach. Springer-Verlag, Heidelberg, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Evolution of non-uniform cellular automata using a genetic algorithm: diversity and computation

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