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Stochastic evolutionary public goods game with first and second order costly punishments in finite populations

机译:有限人口中一阶和二阶代价昂贵的惩罚性随机进化公共物品博弈

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We study the stochastic evolutionary public goods game with punishment in a finite size population.Two kinds of costly punishments are considered,i.e.,first-order punishment in which only the defectors are punished,and second-order punishment in which both the defectors and the cooperators who do not punish the defective behaviors are punished.We focus on the stochastic stable equilibrium of the system.In the population,the evolutionary process of strategies is described as a finite state Markov process.The evolutionary equilibrium of the system and its stochastic stability are analyzed by the limit distribution of the Markov process.By numerical experiments,our findings are as follows.(i) The first-order costly punishment can change the evolutionary dynamics and equilibrium of the public goods game,and it can promote cooperation only when both the intensity of punishment and the return on investment parameters are large enough.(ii)Under the first-order punishment,the further imposition of the second-order punishment cannot change the evolutionary dynamics of the system dramatically,but can only change the probability of the system to select the equilibrium points in the "C+P" states,which refer to the co-existence states of cooperation and punishment.The second-order punishment has limited roles in promoting cooperation,except for some critical combinations of parameters.(iii) When the system chooses "C+P" states with probability one,the increase of the punishment probability under second-order punishment will further increase the proportion of the "P" strategy in the "C+P" states.
机译:我们研究了在有限种群中具有惩罚的随机演化公共物品博弈。考虑了两种代价高昂的惩罚,即仅对叛逃者进行惩罚的一阶惩罚,以及对叛逃者和叛逃者都进行惩罚的二阶惩罚。不惩罚不良行为的合作者将受到惩罚。我们关注系统的随机稳定平衡。在总体中,策略的演化过程被描述为有限状态马尔可夫过程。系统的演化平衡及其随机稳定性通过数值实验,分析了我们的发现。(i)一阶代价高昂的惩罚可以改变公共物品博弈的演化动力和平衡,只有在以下情况下才能促进合作惩罚的强度和投资回报率参数都足够大。(ii)在一阶惩罚下,进一步施加二阶惩罚的n不能显着改变系统的演化动力学,而只能改变系统选择处于“ C + P”状态的平衡点的概率,这是指合作的共存状态除了一些关键的参数组合外,二阶惩罚在促进合作方面的作用有限。(iii)当系统选择概率为“ C + P”的状态时,二阶惩罚的概率增加惩罚将进一步增加“ C + P”状态下“ P”策略的比例。

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  • 来源
    《中国物理:英文版》 |2018年第6期|117-124|共8页
  • 作者单位

    School of Management, Wuhan University of Technology, Wuhan 430070, China;

    School of Science, Wuhan University of Technology, Wuhan 430070, China;

    School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China;

    School of Economics and Management, Wuhan University, Wuhan 430072, China;

    School of Management, Wuhan University of Technology, Wuhan 430070, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
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