19 citations · 31 across the 5 of their papers we have counts for
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cs.LG2020
Randomized Policy Learning for Continuous State and Action MDPs
Hiteshi Sharma, Rahul Jain
Deep reinforcement learning methods have achieved state-of-the-art results in a variety of challenging, high-dimensional domains ranging from video games to locomotion. The key to…
cs.LG2019★ 19 cited
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…