Worst-case efficiency ratio in false-name-proof combinatorial auction mechanisms

Atsushi Iwasaki, Vincent Conitzer, Yoshifusa Omori, Yuko Sakurai, Taiki Todo, Mingyu Guo, Makoto Yokoo

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

25 被引用数 (Scopus)

抄録

This paper analyzes the worst-case efficiency ratio of false-name-proof combinatorial auction mechanisms. False-name-proofness generalizes strategy-proofness by assuming that a bidder can submit multiple bids under fictitious identifiers. Even the well-known Vickrey-Clarke-Groves mechanism is not false-name-proof. It has previously been shown that there is no false-name-proof mechanism that always achieves a Pareto efficient allocation. Consequently, if false-name bids are possible, we need to sacrifice efficiency to some extent. This leaves the natural question of how much surplus must be sacrificed. To answer this question, this paper focuses on worst-case analysis. Specifically, we consider the fraction of the Pareto efficient surplus that, we obtain and try to maximize this fraction in the worst-case, under the constraint of false-name-proofness. As far as we are aware, this is the first attempt to examine the worst-case efficiency of false-name-proof mechanisms. We show that the worst-case efficiency ratio of any false-name-proof mechanism that satisfies some apparently minor assumptions is at most 2/(m +1) for auctions with m different goods. We also observe that the worst-case efficiency ratio of existing false-name-proof mechanisms is generally 1/m or 0. Finally, we propose a novel mechanism, called the adaptive reserve price mechanism that is falso-nanic-proof when all bidders are single-minded. The worst-case efficiency ratio is 2/(m + 1), i.e., optimal.

本文言語英語
ホスト出版物のタイトル9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010
出版社International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
ページ633-640
ページ数8
ISBN(印刷版)9781617387715
出版ステータス出版済み - 1 1 2010
イベント9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010 - Toronto, ON, カナダ
継続期間: 5 10 2010 → …

出版物シリーズ

名前Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
1
ISSN(印刷版)1548-8403
ISSN(電子版)1558-2914

その他

その他9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010
国/地域カナダ
CityToronto, ON
Period5/10/10 → …

All Science Journal Classification (ASJC) codes

  • 人工知能

引用スタイル