activity
20192026
most citedSMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

103 citations · 217 across the 16 of their papers we have counts for

collaborators
Showing 2022Show all

2 papers · 1 filter

cs.GT2022★ 3 cited

Efficient Policy Space Response Oracles

Ming Zhou, Jingxiao Chen, Ying Wen +4

Policy Space Response Oracle methods (PSRO) provide a general solution to learn Nash equilibrium in two-player zero-sum games but suffer from two drawbacks: (1) the computation ine…

cs.LG2022★ 1 cited

Generative Adversarial Exploration for Reinforcement Learning

Weijun Hong, Menghui Zhu, Minghuan Liu +4

Exploration is crucial for training the optimal reinforcement learning (RL) policy, where the key is to discriminate whether a state visiting is novel. Most previous work focuses o…