Automatic core design using reinforcement learning

Yoko Kobayashi, Eitaro Aiyoshi

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper deals with the application of multi-agents algorithm to the core design tool in a nuclear industry. We develop an original solution algorithm for the automatic core design of boiling water reactor using multi-agents and reinforcement learning. The characteristics of this algorithm are that the coupling structure and the coupling operation suitable for the assigned problem are assumed, and an optimal solution is obtained by mutual interference in multi state transitions using multi-agents. We have already proposed an integrated optimization algorithm using a two-stage genetic algorithm for the automatic core design. The objective of this approach is to improve the convergence performance of the optimization in the automatic core design. We compared the results of the proposed technique using multi-agents algorithm with the two-stage genetic algorithm that had been proposed before. The proposed technique is shown to be effective in reducing the iteration numbers in the search process.

本文言語English
ホスト出版物のタイトルProceedings of the 2004 American Control Conference (AAC)
ページ5784-5789
ページ数6
DOI
出版ステータスPublished - 2004 11 29
イベントProceedings of the 2004 American Control Conference (AAC) - Boston, MA, United States
継続期間: 2004 6 302004 7 2

出版物シリーズ

名前Proceedings of the American Control Conference
6
ISSN(印刷版)0743-1619

Other

OtherProceedings of the 2004 American Control Conference (AAC)
国/地域United States
CityBoston, MA
Period04/6/3004/7/2

ASJC Scopus subject areas

  • 電子工学および電気工学

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