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Continuous Spatial Public Goods Game Based on Particle Swarm Optimization with Memory Stability

Author

Listed:
  • Shuo Wang

    (School of Software, Yunnan University, Kunming 650504, China)

  • Zhuang Li

    (School of Software, Yunnan University, Kunming 650504, China)

  • Weidong Li

    (School of Mathematics and Statistics, Yunnan University, Kunming 650504, China)

  • Hua Jiang

    (School of Software, Yunnan University, Kunming 650504, China)

Abstract

Public goods games have been extensively studied to determine the mechanism behind cooperation in social dilemmas. Previous public goods games based on particle swarm algorithms enabled individuals to integrate their past best strategies with the current best strategies of their neighbors, which can effectively promote cooperation. In this paper, we introduce the concept of memory stability and explore the effects of different memory stability coefficients on strategy distribution, strategy update rate, and average cooperation level. Our simulation results showed that, in the case of a very high propensity coefficient, infinite memory stability coefficients cannot reach a high level of cooperation, while reducing memory stability can reach a very high level of cooperation. At a low enhancement factor, weakening memory stability decreased the average cooperation level, while at a higher enhancement factor, a weakening memory stability greatly increased the average group cooperation level. Our study provides new insights into the application of particle swarm algorithms to public goods games.

Suggested Citation

  • Shuo Wang & Zhuang Li & Weidong Li & Hua Jiang, 2022. "Continuous Spatial Public Goods Game Based on Particle Swarm Optimization with Memory Stability," Mathematics, MDPI, vol. 10(23), pages 1-16, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4572-:d:991770
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    References listed on IDEAS

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