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cs.LG2024
Provable Policy Gradient Methods for Average-Reward Markov Potential Games
Min Cheng, Ruida Zhou, P. R. Kumar +1
We study Markov potential games under the infinite horizon average reward criterion. Most previous studies have been for discounted rewards. We prove that both algorithms based on…
cs.LG2023
Value-Biased Maximum Likelihood Estimation for Model-based Reinforcement Learning in Discounted Linear MDPs
Yu-Heng Hung, Ping-Chun Hsieh, Akshay Mete +1
We consider the infinite-horizon linear Markov Decision Processes (MDPs), where the transition probabilities of the dynamic model can be linearly parameterized with the help of a p…