13 citations · 29 across the 14 of their papers we have counts for
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cs.LG2022★ 1 cited
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games
Zihan Ding, Dijia Su, Qinghua Liu +1
This paper proposes new, end-to-end deep reinforcement learning algorithms for learning two-player zero-sum Markov games. Different from prior efforts on training agents to beat a…
cs.LG2021★ 3 cited
Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning
Jie Ren, Yewen Li, Zihan Ding +2
Deep reinforcement learning (DRL) has successfully solved various problems recently, typically with a unimodal policy representation. However, grasping distinguishable skills for s…
cs.LG2018
Deep Reinforcement Learning for Intelligent Transportation Systems
Xiao-Yang Liu, Zihan Ding, Sem Borst +1
Intelligent Transportation Systems (ITSs) are envisioned to play a critical role in improving traffic flow and reducing congestion, which is a pervasive issue impacting urban areas…