Enhancing the Computational Mechanics of Cellular Automata

Author:

Iclănzan David,Gog Anca,Chira Camelia

Publisher

Springer Berlin Heidelberg

Reference31 articles.

1. Andre, D., Bennett III, F.H., Koza, J.R.: Discovery by genetic programming of a cellular automata rule that is better than any known rule for the majority classification problem. In: Proceedings of the First Annual Conference on Genetic Programming, GECCO 1996, pp. 3–11. MIT Press, Cambridge (1996)

2. Chira, C., Gog, A., Lung, R., Iclanzan, D.: Complex Systems and Cellular Automata Models in the Study of Complexity. In: Studia Informatica series, vol. LV(4), pp. 33–49 (2010)

3. Lecture Notes in Computer Science;R. Das,1994

4. de Oliveira, P.P.B., Bortot, J.C., Oliveira, G.: The best currently known class of dynamically equivalent cellular automata rules for density classification. Neurocomputing 70(1-3), 35–43 (2006)

5. Ferreira, C.: Gene Expression Programming: A New Adaptive Algorithm for Solving Problems. Complex Systems 13(2), 87–129 (2001)

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