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High-quality data plays a central role in ensuring the accuracy of policyevaluation. This paper initiates the study of efficient and safe datacollection for bandit policy evaluation. We formulate the problem andinvestigate its several representative variants. For each variant, we analyzeits statistical properties, derive the corresponding exploration policy, anddesign an efficient algorithm for computing it. Both theoretical analysis andexperiments support the usefulness of the proposed methods.

Safe Exploration for Efficient Policy Evaluation and Comparison