Making VCG more robust in combinatorial auctions via submodular approximation

Makoto Yokoo, Atsushi Iwasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The Vickrey-Clarke-Groves (VCG) protocol is a theoretically well-founded protocol that can be used for combinatorial auctions. However, the VCG has several limitations such as (a) vulnerability to false-name bids, (b) vulnerability to loser collusion, and (c) the outcome is not in the core. Yokoo, Matsutani, & Iwasaki (2006) presented a new combinatorial auction protocol called the Groves Mechanism with SubModular Approximation (GM-SMA). This protocol satisfies the following characteristics: (1) it is false-name-proof, (2) each winner is included in a Pareto efficient allocation, and (3) as long as a Pareto efficient allocation is achieved, the protocol is robust against the collusion of losers and the outcome is in the core. The GM-SMA is the first protocol that satisfies all three of these characteristics. The basic ideas of the GM-SMA are as follows: (i) it is based on the VCG protocol, i.e., the payment of a winner in this protocol is identical to the payment in one instance of the Groves mechanism, which is a class of protocols that includes the VCG, (ii) when calculating the payment of a bidder, we approximate the valuations of other bidders by using a submodular valuation function (submodular approximation). This paper shows a high-level presentation of the GM-SMA protocol, and discusses open problems and the relationship to other works in AI.

Original languageEnglish
Title of host publicationAAAI-07/IAAI-07 Proceedings
Subtitle of host publication22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Pages1679-1682
Number of pages4
Publication statusPublished - Nov 28 2007
EventAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference - Vancouver, BC, Canada
Duration: Jul 22 2007Jul 26 2007

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Other

OtherAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
CountryCanada
CityVancouver, BC
Period7/22/077/26/07

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cite this

Yokoo, M., & Iwasaki, A. (2007). Making VCG more robust in combinatorial auctions via submodular approximation. In AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference (pp. 1679-1682). (Proceedings of the National Conference on Artificial Intelligence; Vol. 2).