Log In Sign Up

Population games on dynamic community networks

by   Alain Govaert, et al.

In this letter, we deal with evolutionary game theoretic learning processes for population games on networks with dynamically evolving communities. Specifically, we propose a novel mathematical framework in which a deterministic, continuous-time replicator equation on a community network is coupled with a closed dynamic flow process between communities that is governed by an environmental feedback mechanism, resulting in co-evolutionary dynamics. Through a rigorous analysis of the system of differential equations obtained, we characterize the equilibria of the coupled dynamical system. Moreover, for a class of population games with two actions and symmetric rewards a Lyapunov argument is employed to establish an evolutionary folk theorem that guarantees convergence to the evolutionary stable states of the game. Numerical simulations are provided to illustrate and corroborate our findings.


page 1

page 2

page 3

page 4


Dynamic population games

In this paper, we define a new class of dynamic games played in large po...

Creolizing the Web

The evolution of language has been a hotly debated subject with contradi...

Imitation dynamics in population games on community networks

We study the asymptotic behavior of deterministic, continuous-time imita...

The Evolutionary Dynamics of Independent Learning Agents in Population Games

Understanding the evolutionary dynamics of reinforcement learning under ...

Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games

Evolutionary game theory has been a successful tool to combine classical...

A Unified Perspective of Evolutionary Game Dynamics Using Generalized Growth Transforms

In this paper, we show that different types of evolutionary game dynamic...

Evolutionary rates of information gain and decay in fluctuating environments

In this paper, we wish to investigate the dynamics of information transf...