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2020 A unified approach for solving sequential selection problems
Alexander Goldenshluger, Yaakov Malinovsky, Assaf Zeevi
Probab. Surveys 17(none): 214-256 (2020). DOI: 10.1214/19-PS333

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.

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Alexander Goldenshluger. Yaakov Malinovsky. Assaf Zeevi. "A unified approach for solving sequential selection problems." Probab. Surveys 17 214 - 256, 2020. https://doi.org/10.1214/19-PS333

Information

Received: 1 May 2019; Published: 2020
First available in Project Euclid: 27 April 2020

Digital Object Identifier: 10.1214/19-PS333

Subjects:
Primary: 60G40
Secondary: 62L15

JOURNAL ARTICLE
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Vol.17 • 2020
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