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46

UC
2005
Springer

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Using Genetic Algorithms to Evolve Behavior in Cellular Automata

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Using Genetic Algorithms to Evolve Behavior in Cellular Automata

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Abstract. It is an unconventional computation approach to evolve solutions instead of calculating them. Although using evolutionary computation in computer science dates back to the 1960s, using an evolutionary approach to program other algorithms is not that well known. In this paper a genetic algorithm is used to evolve behavior in cellular automata. It shows how this approach works for diﬀerent topologies and neighborhood shapes. Some diﬀerent one dimensional neighborhood shapes are investigated with the genetic algorithm and yield surprisingly good results.

Thomas Bäck, Ron Breukelaar

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Added	28 Jun 2010
Updated	28 Jun 2010
Type	Conference
Year	2005
Where	UC
Authors	Thomas Bäck, Ron Breukelaar

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