论文标题

网络协调驱动隔离并增强帕累托在协调游戏中的最佳均衡选​​择

Network coevolution drives segregation and enhances Pareto optimal equilibrium selection in coordination games

论文作者

Casado, Miguel A. González, Sánchez, Angel, Miguel, Maxi San

论文摘要

在这项工作中,我们评估了互动网络的动态适应,在玩协调游戏,达到全球协调和均衡选择中所起的作用。具体而言,我们分析了一个协同进化模型,该模型将代理动作的变化与网络动态结合在一起,以便在代理玩游戏时,他们能够切断当前的某些连接并与他人建立联系。我们专注于两个更新规则:复制器动力学(RD)和无条件模仿(UI)。我们研究了一个纯粹的协调游戏(PCG),其中选择是等效的,并且在一般协调游戏(GCG)上,为此采取了风险以风险为主的动作和付款优势。网络可塑性是通过重新连接的概率来衡量的。更改此塑性参数,从一个策略中进行了一个过渡,在该方案中,系统在单个连接组件中完全协调到一个制度,在该制度中,系统片段中的两个连接组件中的片段,每个组件中的每个动作都在不同的动作上协调(如果两个动作都是等效的)。对于不同的更新规则,这种碎片转换的性质是不同的。其次,我们发现,对于GCG中的RD和UI,在片段化跃迁之前,都有一个中间值的塑性,为此,系统能够在付款支持动作中在单个组件网络中完全坐标,i。例如,共同进化增强了两个更新规则的回报优势均衡选择。

In this work we assess the role played by the dynamical adaptation of the interactions network, among agents playing Coordination Games, in reaching global coordination and in the equilibrium selection. Specifically, we analyze a coevolution model that couples the changes in agents' actions with the network dynamics, so that while agents play the game, they are able to sever some of their current connections and connect with others. We focus on two update rules: Replicator Dynamics (RD) and Unconditional Imitation (UI). We investigate a Pure Coordination Game (PCG), in which choices are equivalent, and on a General Coordination Game (GCG), for which there is a risk-dominant action and a payoff-dominant one. The network plasticity is measured by the probability to rewire links. Changing this plasticity parameter, there is a transition from a regime in which the system fully coordinates in a single connected component to a regime in which the system fragments in two connected components, each one coordinated on a different action (either if both actions are equivalent or not). The nature of this fragmentation transition is different for different update rules. Second, we find that both for RD and UI in a GCG, there is a regime of intermediate values of plasticity, before the fragmentation transition, for which the system is able to fully coordinate in a single component network on the payoff-dominant action, i. e., coevolution enhances payoff-dominant equilibrium selection for both update rules.

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