Abstract
This paper proposes a chaotic evolutionary computation algorithm instead of conventional GA (Genetic Algorithm) for such intelligent agents as welfare robots which assist humans. This evolutionary computation is realized by applying chaotic retrieval and Soft DNA(Soft computing oriented Data driven fuNctional scheduling Architecture) on associative memories. We apply this evolutionary computation to multi- agent robots which move abreast and ITS(Intelligent Transport System). Essentially, the process of this evolutionary computation is parallel processing. Therefore, we implement its parallel processing algorithm on A-NET (Actors NETwork) parallel object-oriented computer, and show the usefulness of parallel processing for proposed evolutionary computation.KeywordsEvolutionary ComputationAssociative MemoryIntelligent AgentBidirectional Associative MemoryIntelligent Transport SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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