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Roadmap and research issues of multiagent social simulation using high-performance computing

Author

Listed:
  • Itsuki Noda

    (Artificial Intelligence Research Center, AIST)

  • Nobuyasu Ito

    (The University of Tokyo)

  • Kiyoshi Izumi

    (The University of Tokyo)

  • Hideki Mizuta

    (IBM Japan, Ltd.)

  • Tomio Kamada

    (Kobe University)

  • Hiromitsu Hattori

    (Ritsumeikan University)

Abstract

In this article, we present roadmaps and research issues pertaining to multiagent social simulation to illustrate the directions of technological achievements in that domain. Compared with physical simulation, social simulation is still in the phase of establishing simulation models. We focus on four issues, namely “undetermined model”, “awareness effects”, “obscure boundary”, and “incomplete data”, and consider ways to overcome these issues using the massive computational power of high-performance computing. We select three applications, namely evacuation, road traffic, and market, and estimate the required computational cost of real applications. Moreover, we investigate research issues on the application side and categorize possible future works on multiagent social simulations.

Suggested Citation

  • Itsuki Noda & Nobuyasu Ito & Kiyoshi Izumi & Hideki Mizuta & Tomio Kamada & Hiromitsu Hattori, 2018. "Roadmap and research issues of multiagent social simulation using high-performance computing," Journal of Computational Social Science, Springer, vol. 1(1), pages 155-166, January.
    • Handle: RePEc:spr:jcsosc:v:1:y:2018:i:1:d:10.1007_s42001-017-0011-8
    DOI: 10.1007/s42001-017-0011-8
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    Cited by:

    1. Daigo Umemoto & Nobuyasu Ito, 2019. "Large-scale parallel execution of urban-scale traffic simulation and its performance on K computer," Journal of Computational Social Science, Springer, vol. 2(1), pages 97-101, January.

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