Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing

12 Feb 2020Ge LiuRui WuHeng-Tze ChengJing WangJayden OoiLihong LiAng LiWai Lok Sibon LiCraig BoutilierEd Chi

Deep Reinforcement Learning (RL) is proven powerful for decision making in simulated environments. However, training deep RL model is challenging in real world applications such as production-scale health-care or recommender systems because of the expensiveness of interaction and limitation of budget at deployment... (read more)

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