Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP

no code implementations • 1 Dec 2022 • Jinghan Wang, Mengdi Wang, Lin F. Yang

This work considers the sample complexity of obtaining an $\varepsilon$-optimal policy in an average reward Markov Decision Process (AMDP), given access to a generative model (simulator).