Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
Yao Yao,Li Xiao,Zhicheng An,Wanpeng Zhang,Dijun Luo,Yao Yao,Li Xiao,Zhicheng An,Wanpeng Zhang,Dijun Luo
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 issues, such as planning efficient explorations to learn more accurate dynamic models, evaluating the uncertainty of the learned models, and more rational utilization of models. To mitigate these issues, we present MEEE, a...
