Approximating the Qualitative Vickrey auction by a negotiation protocol

Koen V. Hindriks*, Dmytro Tykhonov, Mathijs De Weerdt

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


A result of Bulow and Klemperer has suggested that auctions may be a better tool to obtain an efficient outcome than negotiation. For example, some auction mechanisms can be shown to be efficient and strategy-proof. However, they generally also require that the preferences of at least one side of the auction are publicly known. However, sometimes it is very costly, impossible, or undesirable to publicly announce such preferences. It thus is interesting to find methods that do not impose this constraint but still approximate the outcome of the auction. In this paper we show that a multi-round multi-party negotiation protocol may be used to this end if the negotiating agents are capable of learning opponent preferences. The latter condition can be met by current state of the art negotiation technology. We show that this protocol approximates the theoretical outcome predicted by a so-called Qualitative Vickrey auction mechanism (even) on a complex multi-issue domain.

Original languageEnglish
Title of host publicationAgent-Mediated Electronic Commerce
Subtitle of host publicationDesigning Trading Strategies and Mechanisms for Electronic Markets - IJCAI Workshop, TADA 2009, Selected and Revised Papers
Number of pages14
ISBN (Print)9783642151163
Publication statusPublished - 1 Jan 2010
Externally publishedYes
Event2009 Workshop on Trading Agent Design and Analysis, TADA 2009, Co-located with the IJCAI 2009 Conference - Pasadena, CA, United States
Duration: 13 Jul 200913 Jul 2009

Publication series

NameLecture Notes in Business Information Processing
Volume59 LNBIP
ISSN (Print)1865-1348


Conference2009 Workshop on Trading Agent Design and Analysis, TADA 2009, Co-located with the IJCAI 2009 Conference
Country/TerritoryUnited States
CityPasadena, CA


  • Approximation
  • Bayesian learning
  • Multi-bilateral negotiation
  • Multiattribute auction
  • Procurement
  • Qualitative auction
  • Simulations


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