Promotion of robust cooperation among agents in complex networks by enhanced expectation-of-cooperation strategy

Tomoaki Otsuka*, Toshiharu Sugawara

*この研究の対応する著者

研究成果: Conference contribution

抄録

We present an interaction strategy with reinforcement learning to promote mutual cooperation among agents in complex networks. Networked computerized systems consisting of many agents that are delegates of social entities, such as companies and organizations, are being implemented due to advances in networking and computer technologies. Because the relationships among agents reflect the interaction structures of the corresponding social entities in the real world, social dilemma situations like the prisoner’s dilemma are often encountered. Thus, agents have to learn appropriate behaviors from the long term viewpoint to be able to function properly in the virtual society. The proposed interaction strategy is called the enhanced expectation-of-cooperation (EEoC) strategy and is an extension of our previously proposed strategy for improving robustness against defecting agents and for preventing exploitation by them. Experiments demonstrated that agents using the EEoC strategy can effectively distinguish cooperative neighboring agents from all-defecting (AllD) agents and thus can spread cooperation among EEoC agents and avoid being exploited by AllD agents. Examination of robustness against probabilistically defecting (ProbD) agents demonstrated that EEoC agents can spread and maintain mutual cooperation if the number of ProbD agents is not large. The EEoC strategy is thus simple and useful in actual computerized systems.

本文言語English
ホスト出版物のタイトルComplex Networks and Their Applications VI - Proceedings of Complex Networks 2017 (The 6th International Conference on Complex Networks and Their Applications)
編集者Hocine Cherifi, Chantal Cherifi, Mirco Musolesi, Márton Karsai
出版社Springer Verlag
ページ815-828
ページ数14
ISBN(印刷版)9783319721491
DOI
出版ステータスPublished - 2018
イベント6th International Conference on Complex Networks and Their Applications, Complex Networks 2017 - Lyon, France
継続期間: 2017 11 292017 12 1

出版物シリーズ

名前Studies in Computational Intelligence
689
ISSN(印刷版)1860-949X

Other

Other6th International Conference on Complex Networks and Their Applications, Complex Networks 2017
国/地域France
CityLyon
Period17/11/2917/12/1

ASJC Scopus subject areas

  • 人工知能

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