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My current focus is on sequential models and reinforcement learning. We want to learn rich models and complex policies efficiently in the amount of feedback required.
I'm particularly interested in offline RL, where we have a dataset of previously collected experience, and want to train a policy solely on the dataset without further interaction with the environment. While this is certainly not the end goal, I think this is a fundamental building block of RL and has many real-world applications, so it is an important problem to understand well.
I'm particularly interested in offline RL, where we have a dataset of previously collected experience, and want to train a policy solely on the dataset without further interaction with the environment. While this is certainly not the end goal, I think this is a fundamental building block of RL and has many real-world applications, so it is an important problem to understand well.
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论文共 76 篇作者统计合作学者相似作者
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2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2023): 7553-7560
Cole Gulino,Justin Fu,Wenjie Luo,George Tucker,Eli Bronstein,Yiren Lu, Jean Harb,Xinlei Pan,Yan Wang,Xiangyu Chen,John D. Co-Reyes,Rishabh Agarwal,
arXiv (Cornell University) (2023)
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CoRR (2023)
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arXiv (Cornell University) (2022)
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arXiv (Cornell University) (2022)
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