activity
20182021
most citedSMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

103 citations · 304 across the 18 of their papers we have counts for

collaborators

29 papers

cs.AI2021

Measuring the Non-Transitivity in Chess

Ricky Sanjaya, Jun Wang, Yaodong Yang

It has long been believed that Chess is the \emph{Drosophila} of Artificial Intelligence (AI). Studying Chess can productively provide valid knowledge about complex systems. Althou…

cs.LG20212 cited

Revisiting the Characteristics of Stochastic Gradient Noise and Dynamics

Yixin Wu, Rui Luo, Chen Zhang +2

In this paper, we characterize the noise of stochastic gradients and analyze the noise-induced dynamics during training deep neural networks by gradient-based optimizers. Specifica…

cs.MA20214 cited

A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

Ying Wen, Hui Chen, Yaodong Yang +4

Trust region methods are widely applied in single-agent reinforcement learning problems due to their monotonic performance-improvement guarantee at every iteration. Nonetheless, wh…

cs.MA20219 cited

Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games

Xiangyu Liu, Hangtian Jia, Ying Wen +5

Measuring and promoting policy diversity is critical for solving games with strong non-transitive dynamics where strategic cycles exist, and there is no consistent winner (e.g., Ro…

cs.MA202125 cited

MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning

Ming Zhou, Ziyu Wan, Hanjing Wang +6

Population-based multi-agent reinforcement learning (PB-MARL) refers to the series of methods nested with reinforcement learning (RL) algorithms, which produces a self-generated se…

cs.AI202110 cited

Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment

Tianze Zhou, Fubiao Zhang, Kun Shao +10

Extending transfer learning to cooperative multi-agent reinforcement learning (MARL) has recently received much attention. In contrast to the single-agent setting, the coordination…