16 citations · 36 across the 11 of their papers we have counts for
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cs.LG2023
Active Vision Reinforcement Learning under Limited Visual Observability
Jinghuan Shang, Michael S. Ryoo
In this work, we investigate Active Vision Reinforcement Learning (ActiveVision-RL), where an embodied agent simultaneously learns action policy for the task while also controlling…
cs.LG2022★ 9 cited
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li, Jinghuan Shang, Srijan Das +1
We investigate whether self-supervised learning (SSL) can improve online reinforcement learning (RL) from pixels. We extend the contrastive reinforcement learning framework (e.g.,…
cs.LG2021★ 16 cited
StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
Jinghuan Shang, Kumara Kahatapitiya, Xiang Li +1
Reinforcement Learning (RL) can be considered as a sequence modeling task: given a sequence of past state-action-reward experiences, an agent predicts a sequence of next actions. I…