Dynamic formation on mobile agents and its evolutionary parallel computation

Abstract

Proposes a chaotic evolutionary computation algorithm instead of a conventional 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 intelligent transport systems. 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 the proposed evolutionary computation.