31 citations · 106 across the 14 of their papers we have counts for
Showing 2019 · cs.LGShow all
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cs.LG2019★ 31 cited
Truly Proximal Policy Optimization
Yuhui Wang, Hao He, Chao Wen +1
Proximal policy optimization (PPO) is one of the most successful deep reinforcement-learning methods, achieving state-of-the-art performance across a wide range of challenging task…
cs.LG2019★ 9 cited
Robust Reinforcement Learning in POMDPs with Incomplete and Noisy Observations
Yuhui Wang, Hao He, Xiaoyang Tan
In real-world scenarios, the observation data for reinforcement learning with continuous control is commonly noisy and part of it may be dynamically missing over time, which violat…
cs.LG2019★ 30 cited
Trust Region-Guided Proximal Policy Optimization
Yuhui Wang, Hao He, Xiaoyang Tan +1
Proximal policy optimization (PPO) is one of the most popular deep reinforcement learning (RL) methods, achieving state-of-the-art performance across a wide range of challenging ta…