A Unified Approach for Solving Sequential Selection Problems
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Date
2020-04-27
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Citation of Original Publication
Alexander Goldenshluger. Yaakov Malinovsky. Assaf Zeevi. "A unified approach for solving sequential selection problems." Probab. Surveys 17 (27 April 2020): 214 - 256. https://doi.org/10.1214/19-PS333
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Attribution 4.0 International
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.