2026
Learning in Bayesian Stackelberg Games With Unknown Follower's Types
ICML 2026poster
We study online learning in Bayesian Stackelberg games, where a leader repeatedly interacts with a follower whose unknown private type is independently drawn at each round from an unknown probability distribution. The goal is to design algorithms that minimize the leader's regret with respect to alw…