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RL Unplugged: Benchmarks for Offline Reinforcement Learning

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Abstract

Offline methods for reinforcement learning have the potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus overcoming concerns associated with online data collection in the real-world, including cost, safety, or ethical con...More

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Author
Sergio Gómez Colmenarejo
Sergio Gómez Colmenarejo
Rishabh Agarwal
Rishabh Agarwal
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