Logit dynamics with concurrent updates for local interaction games

Game Theory is the main tool used to model the behavior of agents that are guided by their own objective in contexts where their gains depend also on the choices made by neighboring agents. Game theoretic approaches have been often proposed for modeling phenomena in a complex social network, such as the formation of the social network itself. We are interested in the dynamics that govern such phenomena. In this paper, we study a specific class of randomized update rules called the logit choice function which can be coupled with different selection rules so to give different dynamics. We study how the logit choice function behave in an extreme case of concurrency.