Cyclical behavior of evolutionary dynamics in coordination games with changing payoffs

TL;DR

This paper models how slow changes in payoffs, driven by population behavior, create cyclical dynamics in coordination games with externalities, revealing different behaviors under various evolutionary dynamics.

Contribution

It introduces a two-speed evolution model where payoffs adapt to aggregate behavior, analyzing its impact on cyclical dynamics in coordination games.

Findings

Under best response and logit dynamics with small noise, trajectories form closed orbits.

Large noise levels cause the steady state to become a sink in logit dynamics.

Replicator dynamics lead to unstable spirals and unbounded trajectories.

Abstract

The paper presents a model of two-speed evolution in which the payoffs in the population game (or, alternatively, the individual preferences) slowly adjust to changes in the aggregate behavior of the population. The model investigates how, for a population of myopic agents with homogeneous preferences, changes in the environment caused by current aggregate behavior may affect future payoffs and hence alter future behavior. The interaction between the agents is based on a symmetric two-strategy game with positive externalities and negative feedback from aggregate behavior to payoffs, so that at every point in time the population has an incentive to coordinate, whereas over time the more popular strategy becomes less appealing. Under the best response dynamics and the logit dynamics with small noise levels the joint trajectories of preferences and behavior converge to closed orbits around the unique steady state, whereas for large noise levels the steady state of the logit dynamics becomes a sink. Under the replicator dynamics the unique steady state of the system is repelling and the trajectories are unbounded unstable spirals.