Web: http://arxiv.org/abs/2201.11861

Jan. 31, 2022, 2:11 a.m. | Nathan Lambert, Markus Wulfmeier, William Whitney, Arunkumar Byravan, Michael Bloesch, Vibhavari Dasagi, Tim Hertweck, Martin Riedmiller

cs.LG updates on arXiv.org arxiv.org

Offline Reinforcement Learning (ORL) enablesus to separately study the two
interlinked processes of reinforcement learning: collecting informative
experience and inferring optimal behaviour. The second step has been widely
studied in the offline setting, but just as critical to data-efficient RL is
the collection of informative data. The task-agnostic setting for data
collection, where the task is not known a priori, is of particular interest due
to the possibility of collecting a single dataset and using it to solve several
downstream …

arxiv exploration learning reinforcement learning

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