20 citations · 27 across the 5 of their papers we have counts for
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cs.LG2021
MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning
Wanpeng Zhang, Xi Xiao, Yao Yao +2
Model-based reinforcement learning is a widely accepted solution for solving excessive sample demands. However, the predictions of the dynamics models are often not accurate enough…
cs.LG2021★ 2 cited
Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
Yao Yao, Li Xiao, Zhicheng An +2
Model-based deep reinforcement learning has achieved success in various domains that require high sample efficiencies, such as Go and robotics. However, there are some remaining is…
cs.LG2017★ 4 cited
Cohesion-based Online Actor-Critic Reinforcement Learning for mHealth Intervention
Feiyun Zhu, Peng Liao, Xinliang Zhu +2
In the wake of the vast population of smart device users worldwide, mobile health (mHealth) technologies are hopeful to generate positive and wide influence on people's health. The…