Effects of Interaction and Learning Distance on Cooperation in Evolutionary Games on a Multiplex Network

Yasuyuki Nakamura, Koichi Yasutake, Keiya Ando, Takahiro Tagawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We investigated a two-layered multiplex network in which players interact depending on the social distance between them. The aim of this study is to clarify the effects of multi-layered structure on emergence of cooperation in the prisoner’s dilemma game including social distances, interactions, and learning distances. We found that the increase of learning distance promotes cooperation even on a multiplex network, and a cooperative strategy tends to vanish away with the parameters, which is contract to the Seltzer’s result.

    Original languageEnglish
    Title of host publicationComplex Networks and Their Applications VII - Volume 1 Proceedings The 7th International Conference on Complex Networks and their Applications COMPLEX NETWORKS 2018
    EditorsRenaud Lambiotte, Luis M. Rocha, Pietro Lió, Hocine Cherifi, Luca Maria Aiello, Chantal Cherifi
    PublisherSpringer Verlag
    Pages797-803
    Number of pages7
    ISBN (Print)9783030054106
    DOIs
    Publication statusPublished - 2019
    Event7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018 - Cambridge, United Kingdom
    Duration: Dec 11 2018Dec 13 2018

    Publication series

    NameStudies in Computational Intelligence
    Volume812
    ISSN (Print)1860-949X

    Other

    Other7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018
    Country/TerritoryUnited Kingdom
    CityCambridge
    Period12/11/1812/13/18

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence

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