22 citations · 31 across the 12 of their papers we have counts for
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cs.RO2024
Learning to Drive via Asymmetric Self-Play
Chris Zhang, Sourav Biswas, Kelvin Wong +5
Large-scale data is crucial for learning realistic and capable driving policies. However, it can be impractical to rely on scaling datasets with real data alone. The majority of dr…
cs.RO2023
Learning Realistic Traffic Agents in Closed-loop
Chris Zhang, James Tu, Lunjun Zhang +3
Realistic traffic simulation is crucial for developing self-driving software in a safe and scalable manner prior to real-world deployment. Typically, imitation learning (IL) is use…