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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Promotion of cooperation through co-evolution of networks and strategy in a 2 x 2 game
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Promotion of cooperation through co-evolution of networks and strategy in a 2 x 2 game

机译:在2 x 2游戏中通过网络和策略的共同进化促进合作

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A 2 x 2 game model implemented by co-evolution of both networks and strategies is established. An existing link between two agents is killed through network adaptation, which then establishes a new link to replace it. Strategy is defined as an offer of "cooperation" (C) or "defection" (D) by an agent. Both networks and strategies are synchronously renovated in each simulation time step. After killing the link with the most disadvantageous neighbor, we consider network adaptations that involve rewiring to (1) a randomly selected agent, (2) a proportionally selected agent (through a roulette selection process based on the degrees of respective agents), (3) an agent randomly selected among a set of neighbors of the neighbors, excluding the most disadvantageous neighbor. Several numerical experiments considering various 2 x 2 game classes, including Prisoner's Dilemma (PD), Chicken, Leader, and Hero, reveal that the proposed co-evolution mechanism can solve dilemmas in the PD game class. The result of solving a dilemma is the development of mutual-cooperation reciprocity (R reciprocity), which arises through the emergence of several cooperative hub agents, which have many links in a heterogeneous and assortative social network. However, the co-evolution mechanism seems counterproductive in the case of the Leader and Hero game classes, where alternating reciprocity (ST reciprocity) is more demanding. It is also suggested that the assortative and cluster coefficients of a network affect the emergence of cooperation for R reciprocity.
机译:建立了通过网络和策略共同进化实现的2 x 2游戏模型。两个代理之间的现有链接通过网络适配被杀死,然后网络适配建立了新的链接来替换它。策略定义为代理商提出的“合作”(C)或“叛逃”(D)。在每个仿真时间步中,网络和策略都将同步更新。终止与最不利邻居的链接后,我们考虑进行网络调整,其中涉及重新布线为(1)随机选择的代理,(2)按比例选择的代理(通过基于各个代理的程度的轮盘选择过程),(3 )从邻居的邻居(不包括最不利的邻居)中随机选择的代理。考虑了各种2 x 2游戏类(包括囚徒困境(PD),Chicken,Leader和Hero)的几个数值实验表明,提出的协同进化机制可以解决PD游戏类中的困境。解决难题的结果是相互合作互惠(R reciprocity)的发展,这是由于几个合作枢纽代理的出现而产生的,这些代理在异质和分类的社交网络中有许多联系。但是,在领导者和英雄游戏类的情况下,协同进化机制似乎适得其反,其中交替互惠(ST互惠)的要求更高。还建议网络的分类系数和聚类系数会影响R互惠合作的出现。

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