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Found 3 papers, 1 papers with code
Federated Offline Reinforcement Learning
Extensive simulations demonstrate the effectiveness of the proposed algorithm.
Semi-Supervised Off Policy Reinforcement Learning
2) The surrogate variables we leverage in the modified SSL framework are predictive of the outcome but not informative to the optimal policy or value function.
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
However, the adoption of such policies in practice is often challenging, as they are hard to interpret within the application context, and lack measures of uncertainty for the learned policy value and its decisions.
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