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A Matrix Approach to the Modeling and Analysis of Network Evolutionary Games with Mixed Strategy Updating Rules

Author

Listed:
  • Yalin Gui

    (Institute of Intelligent Systems and Decision, Wenzhou University, Wenzhou 325035, China)

  • Chengyuan Du

    (Institute of Intelligent Systems and Decision, Wenzhou University, Wenzhou 325035, China)

  • Lixin Gao

    (Institute of Intelligent Systems and Decision, Wenzhou University, Wenzhou 325035, China)

Abstract

So far, most studies on networked evolutionary game have focused on a single update rule. This paper investigated the seeking of the Nash Equilibrium and strategy consensus of the evolutionary networked game with mixed updating rules. First, we construct the algebraic formulation for the dynamics of the evolutionary networked game by using the semi-tensor product method. Second, based on the algebraic form, the dynamic behavior of networked evolutionary games is discussed, and an algorithm to seek the Nash equilibrium is proposed. Third, we investigate the strategy consensus problem for a special networked evolutionary game. Finally, some illustrative examples are given to verify our conclusions.

Suggested Citation

  • Yalin Gui & Chengyuan Du & Lixin Gao, 2022. "A Matrix Approach to the Modeling and Analysis of Network Evolutionary Games with Mixed Strategy Updating Rules," Mathematics, MDPI, vol. 10(19), pages 1-13, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3612-:d:932111
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    References listed on IDEAS

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    3. Zhang, Jianlei & Chen, Xiaojie & Zhang, Chunyan & Wang, Long & Chu, Tianguang, 2010. "Elimination mechanism promotes cooperation in coevolutionary prisoner’s dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4081-4086.
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