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Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game

机译:永不停息​​的学习促进了空间囚徒困境游戏中的合作

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摘要

Holding on to one's strategy is natural and common if the later warrants success and satisfaction. This goes against widespread simulation practices of evolutionary games, where players frequently consider changing their strategy even though their payoffs may be marginally different than those of the other players. Inspired by this observation, we introduce an aspiration-based win-stay-lose-learn strategy updating rule into the spatial prisoner's dilemma game. The rule is simple and intuitive, foreseeing strategy changes only by dissatisfied players, who then attempt to adopt the strategy of one of their nearest neighbors, while the strategies of satisfied players are not subject to change. We find that the proposed win-stay-lose-learn rule promotes the evolution of cooperation, and it does so very robustly and independently of the initial conditions. In fact, we show that even a minute initial fraction of cooperators may be sufficient to eventually secure a highly cooperative final state. In addition to extensive simulation results that support our conclusions, we also present results obtained by means of the pair approximation of the studied game. Our findings continue the success story of related win-stay strategy updating rules, and by doing so reveal new ways of resolving the prisoner's dilemma.
机译:坚持一个人的策略是自然而普遍的,如果后者需要成功和满足的话。这与进化游戏的普遍模拟做法背道而驰,在进化游戏中,玩家的收益经常与其他玩家略有不同,因此他们经常考虑改变策略。受此观察的启发,我们将基于志向的赢-输-走-学习策略更新规则引入到空间囚犯的困境游戏中。该规则简单直观,可以预见只有不满意的玩家才能改变策略,然后他们会尝试采用其最近邻居之一的策略,而满意的玩家的策略则不会改变。我们发现,拟议的“不输则走”学习规则促进了合作的发展,并且非常健壮且独立于初始条件。实际上,我们表明,即使是一小部分初始合作者,也足以最终确保高度合作的最终状态。除了支持我们结论的大量模拟结果外,我们还介绍了通过对博弈的对近似获得的结果。我们的发现延续了相关的“获胜策略”更新规则的成功案例,并以此揭示了解决囚徒困境的新方法。

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