Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games

no code implementations • 15 Dec 2021 • Zuguang Gao, Qianqian Ma, Tamer Başar, John R. Birge

With linear function approximation, the results are for convergence to a linear approximated equilibrium - a new notion of equilibrium that we propose - which describes that each agent's policy is a best reply (to other agents) within a linear space.

Multi-agent Reinforcement Learning Q-Learning