Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising gam...
Constantinos Daskalakis, Rafael Frongillo, Christo...
We consider network congestion problems between TCP flows and define a new game, the Window-game, which models the problems of network congestion caused by the competing flows. An...
Pavlos S. Efraimidis, Lazaros Tsavlidis, George B....
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Finding approximate Nash equilibria in n × n bimatrix games is currently one of the main open problems in algorithmic game theory. Motivated in part by the lack of progress on wo...
As defined by Aumann in 1959, a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for loa...