On imitation dynamics in population games with Markov switching

Abstract

Imitation dynamics in population games are a class of evolutionary game-theoretic models, widely used to study decision-making processes in social groups. Different from other models, imitation dynamics allow players to have minimal information on the structure of the game they are playing, and are thus suitable for many applications, including traffic management, marketing, and disease control. In this work, we study a general case of imitation dynamics where the structure of the game and the imitation mechanisms change in time due to external factors, such as weather conditions or social trends. These changes are modeled using a continuoustime Markov jump process. We present tools to identify the dominant strategy that emerges from the dynamics through methodological analysis of the function parameters. Numerical simulations are provided to support our theoretical findings.

Evolutionary dynamics under periodic switching of update rules in structured populations

“…Due to periodic changes in the environment [28]- [30] or driven by their periodic behavior modes [31]- [33], they may periodically switch their strategy update rules. In addition, the basic idea of switching has been introduced into evolutionary games [34]- [36]. For example, Hilbe et al studied evolutionary dynamics of cooperation in stochastic games where the game structure can be periodically switched [37].…”