Optimization algorithm using multi-agents and reinforcement learning

Yoko Kobayashi, Eitaro Aiyoshi

研究成果: Conference contribution

抄録

This paper deals with combinatorial optimization of permutation type using multi-agents algorithm (MAA). In order to improve optimization capability, we introduced the reinforcement learning and several processes into this MAA. Optimization capability of this algorithm was compared in traveling salesman problem and it provided better optimization results than the conventional MAA and genetic algorithm.

本文言語English
ホスト出版物のタイトルProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
ページ63-68
ページ数6
出版ステータスPublished - 2004 9 13
イベントProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
継続期間: 2004 6 192004 6 23

出版物シリーズ

名前Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
1

Other

OtherProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
国/地域United States
CityPortland, OR
Period04/6/1904/6/23

ASJC Scopus subject areas

  • 工学(全般)

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