Exploring Contextual Bi-level Reinforcement Learning and Its Applications

This chapter explores contextual bi-level reinforcement learning with an emphasis on the Stackelberg framework, where a leader adjusts rewards and transitions while a follower applies entropy regularization. Through examples like tax and mechanism design, it clarifies the roles of leaders and followers to improve understanding of these concepts.