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Learning in Stackelberg Markov Games
Jun He, Andrew L. Liu, Yihsu Chen
https://arxiv.org/abs/2509.16296 https://arxiv.org/pdf/2509.16296

Learning in Stackelberg Markov Games
Designing socially optimal policies in multi-agent environments is a fundamental challenge in both economics and artificial intelligence. This paper studies a general framework for learning Stackelberg equilibria in dynamic and uncertain environments, where a single leader interacts with a population of adaptive followers. Motivated by pressing real-world challenges such as equitable electricity tariff design for consumers with distributed energy resources (such as rooftop solar and energy stor…