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- W1534977626 abstract "Here we present preliminary results in which a genetic algorithm (GA) is used to evolve one-dimensional binary-state cellular automata (CA) to perform a non-trivial task requiring collective behavior. Using a fitness function that is an average area in the iterative map, the GA discovers rules that produce a period-3 oscillation in the concentration of 1s in the lattice. We study one run in which the final state reached by the best evolved rule consists of a regular pattern plus some defects. The structural organization of the CA dynamics is uncovered using the tools of computational mechanics. PACS: 82.20Wt Computational modeling; simulation." @default.
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- W1534977626 date "2002-01-01" @default.
- W1534977626 modified "2023-10-15" @default.
- W1534977626 title "Evolving One Dimensional Cellular Automata to Perform a Non-Trivial Collective Behavior Task: One Case Study" @default.
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- W1534977626 doi "https://doi.org/10.1007/3-540-46043-8_80" @default.
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