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On (Group) Strategy-Proof Mechanisms without Payment for Facility Location Games

Thang, Nguyen Kim (2010), On (Group) Strategy-Proof Mechanisms without Payment for Facility Location Games, dans Saberi, Amin, Internet and Network Economics 6th International Workshop, WINE 2010, Stanford, CA, USA, December 13-17, 2010, Proceedings, Springer : Berlin, p. 531-538. http://dx.doi.org/10.1007/978-3-642-17572-5_47

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SP-money.pdf (199.7Kb)
Type
Communication / Conférence
Date
2010
Titre du colloque
6th International Workshop on Internet and Network Economics, WINE 2010
Date du colloque
2010-12
Ville du colloque
Stanford
Pays du colloque
États-Unis
Titre de l'ouvrage
Internet and Network Economics 6th International Workshop, WINE 2010, Stanford, CA, USA, December 13-17, 2010, Proceedings
Auteurs de l’ouvrage
Saberi, Amin
Éditeur
Springer
Titre de la collection
Lecture Notes in Computer Science
Numéro dans la collection
6484
Ville d’édition
Berlin
Isbn
978-3-642-17571-8
Nombre de pages
580
Pages
531-538
Identifiant publication
http://dx.doi.org/10.1007/978-3-642-17572-5_47
Métadonnées
Afficher la notice complète
Auteur(s)
Thang, Nguyen Kim
Résumé (EN)
We characterize the performance of strategyproof and group-strategyproof social choice rules, for placing a facility on the nodes of a metric network inhabited by N autonomous self-interested agents. Every agent owns a set of locations and caters to minimization of its cost which is the total distance from the facility to its locations. Agents may misreport their locations, so as to manipulate the outcome. A central authority has a set of allowable locations where the facility could be opened. The authority must devise a mechanism that, given the agents reports, places the facility in an allowable location that minimizes the utilitarian social cost — the sum of agents costs. A mechanism is strategyproof (SP) if no agent may misreport its locations and be better off; it is group-strategyproof (GSP) if no coalition of agents benefits by jointly misreporting their locations The requirement for (G)SP in this setting makes optimum placement of the facility impossible and, therefore, we consider approximation (G)SP mechanisms. For SP mechanisms, we give a simple 3-approximation randomized mechanism and also provide asymptotic lower bounds for different variants. For GSP mechanisms, a (2N + 1)-approximation deterministic GSP mechanism is devised. Although the mechanism is simple, we showed that it is asymptotically optimal up to a constant. Our Ω(N 1 − ε ) lower bound that randomization cannot improve over the approximation factor achieved by the deterministic mechanism, when GSP is required.
Mots-clés
GSP mechanisms; SP mechanisms

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