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High-Confidence Off-Policy (or Counterfactual) Variance Estimation

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 نشر من قبل Yash Chandak
 تاريخ النشر 2021
  مجال البحث الهندسة المعلوماتية
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Many sequential decision-making systems leverage data collected using prior policies to propose a new policy. For critical applications, it is important that high-confidence guarantees on the new policys behavior are provided before deployment, to ensure that the policy will behave as desired. Prior works have studied high-confidence off-policy estimation of the expected return, however, high-confidence off-policy estimation of the variance of returns can be equally critical for high-risk applications. In this paper, we tackle the previously open problem of estimating and bounding, with high confidence, the variance of returns from off-policy data



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