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Theoretical Computer Science
Volume 361, Issues 2-3, 1 September 2006, Pages 329-341
Approximation and Online Algorithms
 
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doi:10.1016/j.tcs.2006.05.017    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier B.V. All rights reserved.

How to whack molesstar, open

Sandra Gutiérreza, 1, E-mail The Corresponding Author, Sven O. Krumkeb, 2, E-mail The Corresponding Author, Nicole Megowc, Corresponding Author Contact Information, E-mail The Corresponding Author and Tjark Vredeveldd, E-mail The Corresponding Author

aEscuela Politécnica Nacional, Facultad de Matemáticas, Quito, Ecuador bUniversity of Kaiserslautern, Department of Mathematics, P.O. Box 3049, 67653 Kaiserslautern, Germany cTechnische Universität Berlin, Strasse des 17. Juni 136, 10623 Berlin, Germany dDepartment of Quantitative Economics, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands

Available online 9 June 2006.

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Abstract

In the classical whack-a-mole game moles that pop up at certain locations must be whacked by means of a hammer before they go under ground again. The goal is to maximize the number of moles whacked. This problem can be formulated as an online optimization problem: requests (moles) appear over time at points in a metric space and must be served (whacked) by a server (hammer) before their deadlines (i.e., before they disappear). An online algorithm learns each request only at its release time and must base its decisions on incomplete information. We study the online whack-a-mole problem (WHAM) on the real line and on the uniform metric space. While on the line no deterministic algorithm can achieve a constant competitive ratio, we provide competitive algorithms for the uniform metric space. Our online investigations are complemented by complexity results for the offline problem.

Keywords: Online algorithms; Competitive analysis; NP-hardness; Dynamic programming


Theoretical Computer Science
Volume 361, Issues 2-3, 1 September 2006, Pages 329-341
Approximation and Online Algorithms
 
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