activity
20182024
most citedSMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

103 citations · 127 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2024

RACon: Retrieval-Augmented Simulated Character Locomotion Control

Yuxuan Mu, Shihao Zou, Kangning Yin +4

In computer animation, driving a simulated character with lifelike motion is challenging. Current generative models, though able to generalize to diverse motions, often pose challe…

cs.MA2023

Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future

Yan Song, He Jiang, Haifeng Zhang +3

Even though Google Research Football (GRF) was initially benchmarked and studied as a single-agent environment in its original paper, recent years have witnessed an increasing focu…

cs.SD2023

Cross-Utterance Conditioned VAE for Speech Generation

Yang Li, Cheng Yu, Guangzhi Sun +8

Speech synthesis systems powered by neural networks hold promise for multimedia production, but frequently face issues with producing expressive speech and seamless editing. In res…

cs.LG2023★ 8 cited

An Empirical Study on Google Research Football Multi-agent Scenarios

Yan Song, He Jiang, Zheng Tian +6

Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open…

cs.AI2023★ 3 cited

Order Matters: Agent-by-agent Policy Optimization

Xihuai Wang, Zheng Tian, Ziyu Wan +3

While multi-agent trust region algorithms have achieved great success empirically in solving coordination tasks, most of them, however, suffer from a non-stationarity problem since…

cs.RO2022

Multi-embodiment Legged Robot Control as a Sequence Modeling Problem

Chen Yu, Weinan Zhang, Hang Lai +3

Robots are traditionally bounded by a fixed embodiment during their operational lifetime, which limits their ability to adapt to their surroundings. Co-optimizing control and morph…