Amélie Heliou

Learning with Bandit Feedback in Potential Games

This paper examines the equilibrium convergence properties of no-regret learning with exponential weights in potential games. To establish convergence with minimal information requirements on the players' side, we focus on two frameworks: the semi-bandit case (where players have access to a noisy es…