189 citations · 390 across the 14 of their papers we have counts for
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cs.LG2022★ 2 cited
Sampling Efficient Deep Reinforcement Learning through Preference-Guided Stochastic Exploration
Wenhui Huang, Cong Zhang, Jingda Wu +3
Massive practical works addressed by Deep Q-network (DQN) algorithm have indicated that stochastic policy, despite its simplicity, is the most frequently used exploration approach.…
cs.LG2021★ 120 cited
Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Driving
Jingda Wu, Zhiyu Huang, Wenhui Huang +1
Reinforcement learning (RL) requires skillful definition and remarkable computational efforts to solve optimization and control problems, which could impair its prospect. Introduci…