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cs.CV2024
When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?
Tongzhou Mu, Zhaoyang Li, Stanisław Wiktor Strzelecki +4
Learning policies from high-dimensional visual inputs, such as pixels and point clouds, is crucial in various applications. Visual reinforcement learning is a promising approach th…
cs.RO2024
Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
Xiu Yuan, Tongzhou Mu, Stone Tao +3
Recent advancements in robot learning have used imitation learning with large models and extensive demonstrations to develop effective policies. However, these models are often lim…