AI RESEARCH

Policy Iteration for Two-Player General-Sum Stochastic Stackelberg Games

arXiv CS.LG

ArXi:2405.06689v2 Announce Type: replace-cross We address two-player general-sum stochastic Stackelberg games (SSGs), where the leader's policy is optimized considering the best-response follower whose policy is optimal for its reward under the leader. Existing policy gradient and value iteration approaches for SSGs do not guarantee monotone improvement in the leader's policy under the best-response follower. Consequently, their performance is not guaranteed when their limits are not stationary Stackelberg equilibria (SSEs), which do not necessarily exist.