Datasets for Data-Driven Reinforcement Learning

Fu Justin
Fu Justin
Nachum Ofir
Nachum Ofir
Cited by: 0|Bibtex|Views26
Other Links: arxiv.org

Abstract:

The offline reinforcement learning (RL) problem, also referred to as batch RL, refers to the setting where a policy must be learned from a dataset of previously collected data, without additional online data collection. In supervised learning, large datasets and complex deep neural networks have fueled impressive progress, but in contra...More

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