Behavior Regularized Offline Reinforcement Learning

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Other Links: arxiv.org

Abstract:

In reinforcement learning (RL) research, it is common to assume access to direct online interactions with the environment. However in many real-world applications, access to the environment is limited to a fixed offline dataset of logged experience. In such settings, standard RL algorithms have been shown to diverge or otherwise yield p...More

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