Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. (arXiv:2210.11942v1 [cs.GT])

Stackelberg Equilibria arise naturally in a range of popular learning
problems, such as in security games or automated mechanism design, and have
received increasing attention in the reinforcement learning literature
recently. We present a general framework for implementing Stackelberg
Equilibria search as a multi-agent RL problem, allowing a wide range of design
choices. We discuss how previous approaches can be seen as specific
instantiations of this framework. As a key insight, we note that the design
space allows for approaches …

arxiv equilibria reinforcement reinforcement learning