Towards a Relation Between Learning Agents and Evolutionary Dynamics

Modeling learning agents in the context of Multi-agent Systems requires insight in the type and form of interactions with the environment and other agents in the system. Usually, these agents are modeled similar to the different players in a standard game theoretical model. In this paper we examine whether evolutionary game theory, and more specifically the replicator dynamics, is an adequate theoretical model for the study of the dynamics of reinforcement learning agents in a multi-agent system. As a first step in this direction we extend the results of [1, 9] to a more general reinforcement learning framework, i.e. Learning Automata.