Cooperation, structure and hierarchy in multiadaptive games

TL;DR

This paper explores how coevolving interaction structures and strategies in multiadaptive games influence cooperation, hierarchy, and stability under various noise conditions, emphasizing the importance of strategy update speed.

Contribution

It generalizes a recent multiadaptive game model to analyze the effects of feedback, noise, and timescale ratios on cooperation and social hierarchy emergence.

Findings

Fast strategy updates promote cooperation.

Certain noise types can eliminate all-cooperator states.

Stable hubs support persistent cooperation.

Abstract

Game-theoretical models where the rules of the game and the interaction structure both coevolves with the game dynamics -- multiadaptive games -- capture very flexible situations where cooperation among selfish agents can emerge. In this work, we will discuss a multiadaptive model presented in a recent Letter [Phys. Rev. Lett. 106, 028702 (2011)], and generalizations of it. The model captures a non-equilibrium situation where social unrest increases the incentive to cooperate and, simultaneously, agents are partly free to influence with whom they interact. First, we investigate the details of how the feedback from the behavior of agents determines the emergence of cooperation and hierarchical contact structures. We also study the stability of the system to different types of noise, and find that different regions of parameter space show very different response. Some types of noise can destroy an all-cooperator state. If, on the other hand, hubs are stable, then so is the all-C state. Finally, we investigate the dependence of the ratio between the timescales of strategy updates and the evolution of the interaction structure. We find that a comparatively fast strategy dynamics is a prerequisite for the emergence of cooperation.