Evolutionary games and the emergence of complex networks

TL;DR

This paper investigates how complex network structures emerge from evolutionary games, specifically the Prisoner's Dilemma, when agents adapt their interaction partners to maximize payoffs, leading to networks with scale-free and small-world properties.

Contribution

It introduces a coevolutionary model where agents adapt their connections in an iterated Prisoner's Dilemma, revealing the emergence of complex network topologies from strategic interactions.

Findings

Networks develop broad degree distributions indicating scale-free behavior.

Emergence of small-world and assortative mixing properties.

System stabilizes at cooperative Nash equilibria with dynamic reorganization.

Abstract

The emergence of complex networks from evolutionary games is studied occurring when agents are allowed to switch interaction partners. For this purpose a coevolutionary iterated Prisoner's Dilemma game is defined on a random network with agents as nodes and games along the links. The agents change their neighborhoods to improve their payoff. The system relaxes to stationary states corresponding to cooperative Nash equilibria with the additional property that no agent can improve its payoff by changing its neighborhood. Small perturbations of the system lead to avalanches of strategy readjustments reestablishing equilibrium. As a result of the dynamics, the network of interactions develops non-trivial topological properties as a broad degree distribution suggesting scale-free behavior, small-world characteristics, and assortative mixing.