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            Universal Off-Policy Evaluation
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            Universal Off-Policy Evaluation

            Dec 6, 2021

            Speakers

            YC

            Yash Chandak

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            SN

            Scott Niekum

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            BCDS

            Bruno C. Da Silva

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            About

            When faced with sequential decision-making problems, it is often useful to be able to predict what would happen if decisions were made using a new policy. Those predictions must often be based on data collected under some previously used decision-making rule. Many previous methods enable such off-policy (or counterfactual) estimation of the _expected_ value of a performance measure called the return. In this paper, we take the first steps towards a 'universal off-policy estimator' (UnO)—one that…

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            NeurIPS 2021

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