A Unified Approach for Solving Sequential Selection Problems
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2019-01-25
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Citation of Original Publication
Alexander Goldenshluger, Yaakov Malinovsky, Assaf Zeevi, A Unified Approach for Solving Sequential Selection Problems, Probability , 2019, https://arxiv.org/abs/1901.04183
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Abstract
In this paper we develop a unified approach for solving a wide class of sequential
selection problems. This class includes, but is not limited to, selection problems with
no–information, rank–dependent rewards, and considers both fixed as well as random
problem horizons. The proposed framework is based on a reduction of the original
selection problem to one of optimal stopping for a sequence of judiciously constructed
independent random variables. We demonstrate that our approach allows exact and
efficient computation of optimal policies and various performance metrics thereof for a
variety of sequential selection problems, several of which have not been solved to date.