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Spatial structure enhanced cooperation in dissatisfied adaptive snowdrift game

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  • Wen Zhang
  • Chen Xu
  • Pak Hui

Abstract

The dissatisfied adaptive snowdrift game (DASG) describes the adaptive actions driven by the level of dissatisfaction when two connected agents interact. We study the DASG in static networks both numerically and analytically. In a random network of uniform degree k, the system evolves into a homogeneous state consisting only of cooperators when the cost-to-benefit ratio r > r 0 and a mixed phase with the coexistence of cooperators and defectors when r > r 0 , where r 0 is a threshold. For an infinite population, the large k limit corresponding to the well-mixed case is solved analytically. A theory is developed based on the pair approximation. It gives the frequency of cooperation f c and the densities of different pairs that are in good agreement with simulation results. The results revealed that f c is enhanced in networked populations with a finite k, when compared with the well-mixed case. The reasons that the theory works well for the present model are traced back to the weak spatial correlation implied by the random network and the fact that the adaptive actions in DASG are driven only by the strategy pairs. The results shed light on the class of models that the pair approximation is applicable. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Wen Zhang & Chen Xu & Pak Hui, 2013. "Spatial structure enhanced cooperation in dissatisfied adaptive snowdrift game," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(5), pages 1-6, May.
    • Handle: RePEc:spr:eurphb:v:86:y:2013:i:5:p:1-6:10.1140/epjb/e2013-30997-2
    DOI: 10.1140/epjb/e2013-30997-2
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    Citations

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    Cited by:

    1. Ye, Wenxing & Feng, Weiying & Lü, Chen & Fan, Suohai, 2017. "Memory-based prisoner’s dilemma game with conditional selection on networks," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 31-37.
    2. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    3. Ye, Wenxing & Fan, Suohai, 2020. "Evolutionary traveler’s dilemma game based on particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    4. Liu, Chengwei & Wang, Juan & Li, Xiaopeng & Xia, Chengyi, 2020. "The link weight adjustment considering historical strategy promotes the cooperation in the spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    5. Dong, Yukun & Xu, Hedong & Fan, Suohai, 2019. "Memory-based stag hunt game on regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 247-255.

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    Keywords

    Statistical and Nonlinear Physics;

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