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Found 2 papers, 1 papers with code
Percentile Criterion Optimization in Offline Reinforcement Learning
The percentile criterion is approximately solved by constructing an \emph{ambiguity set} that contains the true model with high probability and optimizing the policy for the worst model in the set.
Soft-Robust Algorithms for Batch Reinforcement Learning
In reinforcement learning, robust policies for high-stakes decision-making problems with limited data are usually computed by optimizing the percentile criterion, which minimizes the probability of a catastrophic failure.
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