31 citations · 106 across the 14 of their papers we have counts for
4 papers · 1 filter
Stabilizing Q Learning Via Soft Mellowmax Operator
Yaozhong Gan, Zhe Zhang, Xiaoyang Tan
Learning complicated value functions in high dimensional state space by function approximation is a challenging task, partially due to that the max-operator used in temporal differ…
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…
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…
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…