Multiple-world genetic algorithm to identify locally reasonable behaviors in complex social networks

Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara

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

Abstract

We propose a novel method for evolutionary network analysis that uses the genetic algorithm (GA), called the multiple world genetic algorithm, to coevolve appropriate in-dividual behaviors of many agents on complex networks without sacrificing diversity. The GA is the powerful way, and thus, used in many domains, such as economics, biology, and social science as well as computer science, to find the interaction strategies on networks of agents. In evolutionary network analysis using GA, parents for reproduction of offspring are often selected among their neighbors under the assumption that neighbors' better strategies are useful. However, if they are on complex networks, agents exist in distinctive and diverse situations. Therefore, agents have their own appropriate interaction strategies that may be affected by a large number of neighboring agents. Here, we propose the evolutionary computation method that uses a GA on fixed networks to coevolve diverse strategies for individual agents. We conducted the experiments using simulated games of social networking services to evaluate the proposed method. The results indicate that it could effectively evolve the diverse strategy for each agent and the resulting fitness values were almost always larger than those derived through evolution using the conventional evolutionary network analysis using the GA.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3665-3672
Number of pages8
ISBN (Electronic)9781728145693
DOIs
Publication statusPublished - 2019 Oct
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: 2019 Oct 62019 Oct 9

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Conference

Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
CountryItaly
CityBari
Period19/10/619/10/9

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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  • Cite this

    Miura, Y., Toriumi, F., & Sugawara, T. (2019). Multiple-world genetic algorithm to identify locally reasonable behaviors in complex social networks. In 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 (pp. 3665-3672). [8914277] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2019-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2019.8914277