This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
Computing optimal strategies to commit to in general normal-form or Bayesian games is a topic that has recently been gaining attention, in part due to the application of such algo...
We study the convergence times of dynamics in games involving graphical relationships of players. Our model of local interaction games generalizes a variety of recently studied ga...
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...