
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, in 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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Type
Communication / ConférenceDate
2010Conference title
6th International Workshop on Internet and Network Economics, WINE 2010Conference date
2010-12Conference city
StanfordConference country
États-UnisBook title
Internet and Network Economics 6th International Workshop, WINE 2010, Stanford, CA, USA, December 13-17, 2010, ProceedingsBook author
Saberi, AminPublisher
Springer
Series title
Lecture Notes in Computer ScienceSeries number
6484Published in
Berlin
ISBN
978-3-642-17571-8
Number of pages
580Pages
531-538
Publication identifier
Metadata
Show full item recordAuthor(s)
Thang, Nguyen KimAbstract (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.Subjects / Keywords
GSP mechanisms; SP mechanismsRelated items
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