Genetic network programming - application to intelligent agents

H. Katagiri*, K. Hirasawa, J. Hu

*この研究の対応する著者

研究成果: Conference article査読

78 被引用数 (Scopus)

抄録

Recently many studies have been made on automatic design of the complex systems by using the evolutionary optimization techniques such as Genetic Algorithms (GA), Evolution Strategy (ES), Evolutionary Programming (EP) and Genetic Programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as generation of intelligent behavior sequences of robots. In this paper, a new method named Genetic network Programming (GNP) is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain better structure, GNP changes itself by using evolutionary optimization techniques.

本文言語English
ページ(範囲)3829-3834
ページ数6
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
5
出版ステータスPublished - 2000 12月 1
外部発表はい
イベント2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA
継続期間: 2000 10月 82000 10月 11

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ハードウェアとアーキテクチャ

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