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.

翻译：本文评估了协调博弈中智能体之间交互网络的动态适应在达成全局协调和均衡选择中的作用。具体而言，我们分析了一个共进化模型，该模型将智能体的行为变化与网络动力学相结合，使得智能体在博弈过程中能够切断部分现有连接并建立新连接。我们重点关注两种更新规则：复制动力学和无条件模仿。我们研究了纯协调博弈（其中选择等价）和一般协调博弈（其中存在风险主导行动和收益主导行动）。网络可塑性通过重新连接链路的概率来衡量。改变这一可塑性参数，系统会从完全协调于单个连通组件的状态，转变为分裂为两个连通组件的状态，每个组件各自协调于不同行动（无论行动是否等价）。这种分裂转变的性质因更新规则的不同而不同。其次，我们发现，在一般协调博弈中，无论是复制动力学还是无条件模仿，在分裂转变之前存在一个中等可塑性值的区间，在此区间内系统能够在单个组件网络上完全协调于收益主导行动，即共进化增强了两种更新规则下的收益主导均衡选择。