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

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.