Semi-pessimistic pseudo labeling learns a pessimistic reward lower bound from labeled plus unlabeled data and uses it to train offline RL policies, with regret bounds under a weaker semi-coverage condition.
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Semi-pessimistic Reinforcement Learning
Semi-pessimistic pseudo labeling learns a pessimistic reward lower bound from labeled plus unlabeled data and uses it to train offline RL policies, with regret bounds under a weaker semi-coverage condition.