We provide efficient algorithms for finding approximate BayesNash equilibria (BNE) in graphical, specifically tree, games of incomplete information. In such games an agent’s p...
Satinder P. Singh, Vishal Soni, Michael P. Wellman
In this paper we analyze the convergence of independent adaptive learners in repeated games. We show that, in this class of games, independent adaptive learners converge to pure Na...
Fictitious play is a simple learning algorithm for strategic games that proceeds in rounds. In each round, the players play a best response to a mixed strategy that is given by the...
We consider a wireless collision channel, shared by a finite number of users who transmit to a common base station. Each user wishes to minimize its average transmission rate (or p...
A general class of no-regret learning algorithms, called no-Φ-regret learning algorithms, is defined which spans the spectrum from no-external-regret learning to no-internal-reg...