Bayesian auctions with friends and foes

Po-An Chen*, David Kempe

*Corresponding author for this work

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

4 Scopus citations


We study auctions whose bidders are embedded in a social or economic network. As a result, even bidders who do not win the auction themselves might derive utility from the auction, namely, when a friend wins. On the other hand, when an enemy or competitor wins, a bidder might derive negative utility. Such spite and altruism will alter the bidding strategies. A simple and natural model for bidders' utilities in these settings posits that the utility of a losing bidder i as a result of bidder j winning is a constant (positive or negative) fraction of bidder j's utility. We study such auctions under a Bayesian model in which all valuations are distributed independently according to a known distribution, but the actual valuations are private. We describe and analyze Nash Equilibrium bidding strategies in two broad classes: regular friendship networks with arbitrary valuation distributions, and arbitrary friendship networks with identical uniform valuation distributions.

Original languageEnglish
Title of host publicationAlgorithmic Game Theory - Second International Symposium, SAGT 2009, Proceedings
Number of pages12
StatePublished - 2009
Event2nd International Symposium on Algorithmic Game Theory, SAGT 2009 - Paphos, Cyprus
Duration: 18 Oct 200920 Oct 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5814 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Symposium on Algorithmic Game Theory, SAGT 2009


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