Multi Agent Systems with Symbiotic Learning and Evolution -Masbiole- and Its Application.

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  • Hirasawa Kotaro
    Graduate School of Information, Production and Systems, Waseda University.
  • Nakanishi Katsushige
    Graduate School of Information Science and Electrical Engineering, Kyushu University.
  • Eguchi Toru
    Graduate School of Information Science and Electrical Engineering, Kyushu University.
  • Hu Jinglu
    Graduate School of Information Science and Electrical Engineering, Kyushu University.

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Other Title
  • 共生学習進化型マルチエージェントシステムとその応用
  • キョウセイ ガクシュウ シンカガタ マルチエージェント システム ト ソノ オウヨウ

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Abstract

Recently, systems are becoming more complex and larger than ever, so numerous attempts have been made to introduce biological features into artificial systems, because many biological systems in the nature exist as one of the most complex systems.<br>Multi agent system with symbiotic learning and evolution have been recently proposed. It is named Masbiole. In this paper, Masbiole is reviewed and the method for evolving multi agent systems is proposed. From simulations on a multi objective knapsack problem, it has been clarified that Masbiole has better performance than that of conventional multi objective genetic algorithms.

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