Presentation | 2014-07-26 Learning of Mixed-Rule Cellular Automata Based on the Genetic Algorithm Ryo SAWAYAMA, Toshimichi SAITO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper studies the cellular automaton (CA) governed by combination of two rules. First, we analyze a class of CA that generates several isolated spatiotemporal patterns without transient phenomena. Second, we present an evolutionary algorithm that tries to optimize the combination of two rules to stabilize the desired isolated patterns. Performing basic numerical experiments, it is shown that the evolutionary algorithm can make transient phenomena and can stabilize the desired isolated patterns. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Cellular Automata / Genetic Algorism / Return Map |
Paper # | NC2014-19 |
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Committee | NC |
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Conference Date | 2014/7/19(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Learning of Mixed-Rule Cellular Automata Based on the Genetic Algorithm |
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Keyword(1) | Cellular Automata |
Keyword(2) | Genetic Algorism |
Keyword(3) | Return Map |
1st Author's Name | Ryo SAWAYAMA |
1st Author's Affiliation | EE Dept., Hosei University() |
2nd Author's Name | Toshimichi SAITO |
2nd Author's Affiliation | EE Dept., Hosei University |
Date | 2014-07-26 |
Paper # | NC2014-19 |
Volume (vol) | vol.114 |
Number (no) | 154 |
Page | pp.pp.- |
#Pages | 5 |
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