19 citations · 36 across the 7 of their papers we have counts for
3 papers · 1 filter
Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints
Liyu Chen, Rahul Jain, Haipeng Luo
We study regret minimization for infinite-horizon average-reward Markov Decision Processes (MDPs) under cost constraints. We start by designing a policy optimization algorithm with…
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo +2
Model-free reinforcement learning is known to be memory and computation efficient and more amendable to large scale problems. In this paper, two model-free algorithms are introduce…
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
Yi Ouyang, Mukul Gagrani, Ashutosh Nayyar +1
We consider the problem of learning an unknown Markov Decision Process (MDP) that is weakly communicating in the infinite horizon setting. We propose a Thompson Sampling-based rein…