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The effect of stability-based strategy updating on cooperation in evolutionary social dilemmas

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  • Zha, Jiajing
  • Li, Cong
  • Fan, Suohai

Abstract

The stability of payoffs, often depicted by variance, provides more information during the decision-making process. With the help of memory, we propose a stability-based strategy updating rule and study its effect on cooperative behaviors. Under this updating rule, the probability of learning strategy is affected not only by the difference of average payoffs but also the stability. Based on the prisoner’s dilemma game and snowdrift game, simulations show that compared with the Fermi rule, the introduction of stability enhances cooperative behaviors and average payoffs. Moreover, cooperators in population own much higher and more stable payoffs than defectors when considering long memories. Compared with the memory-based rule which considers the difference of average payoffs, the stability-based rule shows these superiorities on cooperators when the payoff parameters are relatively large, which suggests that the proposed rule exhibits its dominant position when the fluctuation of payoffs is obvious. According to this conclusion, we obtain the application scope enhancing cooperators of memory-based and stability-based rules, which maybe helpful in understanding the influence of these two rules on cooperation under different circumstances.

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  • Zha, Jiajing & Li, Cong & Fan, Suohai, 2022. "The effect of stability-based strategy updating on cooperation in evolutionary social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    • Handle: RePEc:eee:apmaco:v:413:y:2022:i:c:s0096300321006871
    DOI: 10.1016/j.amc.2021.126603
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