A novel estimation of distribution algorithm using graph-based chromosome representation and reinforcement learning

Xianneng Li*, Bing Li, Shingo Mabu, Kotaro Hirasawa

*この研究の対応する著者

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

This paper proposed a novel EDA, where a directed graph network is used to represent its chromosome. In the proposed algorithm, a probabilistic model is constructed from the promising individuals of the current generation using reinforcement learning, and used to produce the new population. The node connection probability is studied to develop the probabilistic model, therefore pairwise interactions can be demonstrated to identify and recombine building blocks in the proposed algorithm. The proposed algorithm is applied to a problem of agent control, i.e., autonomous robot control. The experimental results show the superiority of the proposed algorithm comparing with the conventional algorithms.

本文言語English
ホスト出版物のタイトル2011 IEEE Congress of Evolutionary Computation, CEC 2011
ページ37-44
ページ数8
DOI
出版ステータスPublished - 2011
イベント2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA
継続期間: 2011 6 52011 6 8

Other

Other2011 IEEE Congress of Evolutionary Computation, CEC 2011
CityNew Orleans, LA
Period11/6/511/6/8

ASJC Scopus subject areas

  • 計算理論と計算数学
  • 理論的コンピュータサイエンス

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