Replicator dynamics model the interactions and change in large populations of agents. Standard replicator dynamics, however, only allow single action interactions between agents. Complex interactions, as modeled by general extensive games, have received comparatively little attention in this setting. Recently, replicator dynamics have been adapted to extensive-form games represented in sequence...

The replicator-mutator dynamics is a set of differential equations frequently used in biological and socioeconomic contexts to model evolutionary processes subject to mutation, error or experimentation. The replicator-mutator dynamics generalizes the widely used replicator dynamics, which appears in this framework as the extreme case where replication is perfectly precise. This paper studies th...

Multi–agent learning is a challenging open task in artificial intelligence. It is known an interesting connection between multi–agent learning algorithms and evolutionary game theory, showing that the learning dynamics of some algorithms can be modeled as replicator dynamics with a mutation term. Inspired by the recent sequence–form replicator dynamics, we develop a new version of theQ–learning...

In this note, we investigate the relationship between probabilistic updating mechanisms and discrete-time replicator-mutator dynamics. We consider the recently shown connection between Bayesian updating and replicator dynamics and extend it to the replicator-mutator dynamics by considering prediction and filtering recursions in hidden Markov models (HMM). We show that it is possible to understa...