Article

Weak monotonicity suffices for truthfulness on convex domains

Authors:

Michael Saks,

Lan YuAuthors Info & Claims

EC '05: Proceedings of the 6th ACM conference on Electronic commerce

Pages 286 - 293

https://doi.org/10.1145/1064009.1064040

Published: 05 June 2005 Publication History

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Abstract

Weak monotonicity is a simple necessary condition for a social choice function to be implementable by a truthful mechanism. Roberts [10] showed that it is sufficient for all social choice functions whose domain is unrestricted. Lavi, Mu'alem and Nisan [6] proved the sufficiency of weak monotonicity for functions over order-based domains and Gui, Muller and Vohra [5] proved sufficiency for order-based domains with range constraints and for domains defined by other special types of linear inequality constraints. Here we show the more general result, conjectured by Lavi, Mu'alem and Nisan [6], that weak monotonicity is sufficient for functions defined on any convex domain.

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Akbari SKiyavash NSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)Triple changes estimator for targeted policiesProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692098(666-695)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692098
Rochet J(2024)Multidimensional screening after 37 yearsJournal of Mathematical Economics10.1016/j.jmateco.2024.103010113(103010)Online publication date: Aug-2024
https://doi.org/10.1016/j.jmateco.2024.103010
Joswig MKlimm MSpitz S(2024)The polyhedral geometry of truthful auctionsMathematical Programming10.1007/s10107-024-02168-yOnline publication date: 28-Nov-2024
https://doi.org/10.1007/s10107-024-02168-y
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Index Terms

Weak monotonicity suffices for truthfulness on convex domains
1. Applied computing
  1. Electronic commerce
  2. Law, social and behavioral sciences
    1. Economics

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Published In

EC '05: Proceedings of the 6th ACM conference on Electronic commerce

June 2005

302 pages

ISBN:1595930493

DOI:10.1145/1064009

General Chair:
John Riedl
University of Minnesota
,
Program Chairs:
Michael Kearns
University of Pennsylvania
,
Michael Reiter
Carnegie Mellon University, Pittsburgh, PA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 05 June 2005

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EC05: Sixth ACM Conference on Electronic Commerce 2005

June 5 - 8, 2005

BC, Vancouver, Canada

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Overall Acceptance Rate 664 of 2,389 submissions, 28%

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Cited By

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Akbari SKiyavash NSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)Triple changes estimator for targeted policiesProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692098(666-695)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692098
Rochet J(2024)Multidimensional screening after 37 yearsJournal of Mathematical Economics10.1016/j.jmateco.2024.103010113(103010)Online publication date: Aug-2024
https://doi.org/10.1016/j.jmateco.2024.103010
Joswig MKlimm MSpitz S(2024)The polyhedral geometry of truthful auctionsMathematical Programming10.1007/s10107-024-02168-yOnline publication date: 28-Nov-2024
https://doi.org/10.1007/s10107-024-02168-y
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Christodoulou GKoutsoupias EKovacs A(2022)On the nisan-ronen conjectureACM SIGecom Exchanges10.1145/3572885.357288820:1(41-46)Online publication date: 28-Nov-2022
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