Computing Optimal Strategies for a Search Game in Discrete Locations

Consider a two-person zero-sum search game between a hider and a searcher. The hider hides among n discrete locations, and the searcher successively visits individual locations until finding the hider. Known to both players, a search at location i takes t i time units and detects the hider—if hidden there—independently with probability α i , for [Formula: see text]. The hider aims to maximize the expected time until detection, whereas the searcher aims to minimize it. We present an algorithm to compute an optimal strategy for each player. We demonstrate the algorithm’s efficiency in a numerical study, in which we also study the characteristics of the optimal hiding strategy. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: J. Clarkson is grateful for the support of the Engineering & Physical Sciences Research Council STOR-i Centre for Doctoral Training at Lancaster University [Grant EP/L015692/1]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0155 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0155 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

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Publication Details

Journal
INFORMS journal on computing
Published
2024-08-09
DOI
https://doi.org/10.1287/ijoc.2023.0155
Primary Topic
Optimization and Search Problems
Type
article
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article

Computing Optimal Strategies for a Search Game in Discrete Locations

Kyle Y. Lin, Jake Clarkson
INFORMS journal on computing
Optimization and Search Problems
article

Computing Optimal Strategies for a Search Game in Discrete Locations

Kyle Y. Lin, Jake Clarkson
article en

Abstract

Consider a two-person zero-sum search game between a hider and a searcher. The hider hides among n discrete locations, and the searcher successively visits individual locations until finding the hider. Known to both players, a search at location i takes t i time units and detects the hider—if hidden there—independently with probability α i , for [Formula: see text]. The hider aims to maximize the expected time until detection, whereas the searcher aims to minimize it. We present an algorithm to compute an optimal strategy for each player. We demonstrate the algorithm’s efficiency in a numerical study, in which we also study the characteristics of the optimal hiding strategy. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: J. Clarkson is grateful for the support of the Engineering & Physical Sciences Research Council STOR-i Centre for Doctoral Training at Lancaster University [Grant EP/L015692/1]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0155 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0155 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

INFORMS journal on computingVol. 37(3)
Institut national de recherche en sciences et technologies du numérique (FR), Université Côte d'Azur (FR), Naval Postgraduate School (US)
Openalex Percentile: Top 86%
Optimization and Search Problems
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Computing Optimal Strategies for a Search Game in Discrete Locations — Kyle Y. Lin, Jake Clarkson · INFORMS journal on computing (2024) | TGRS Research Map | TGRS