Bayesian combinatorial auctions

George Christodoulou, Annamária Kovács, Michael Schapira

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

We study the following simple Bayesian auction setting:mitems are sold to nselfish bidders inmindependent second-price auctions. Each bidder has a private valuation function that specifies his or her complex preferences over all subsets of items. Bidders only have beliefs about the valuation functions of the other bidders, in the form of probability distributions. The objective is to allocate the items to the bidders in a way that provides a good approximation to the optimal social welfare value.We show that if bidders have submodular or, more generally, fractionally subadditive (aka XOS) valuation functions, every Bayes-Nash equilibrium of the resulting game provides a 2-approximation to the optimal social welfare. Moreover, we show that in the full-information game, a pure Nash always exists and can be found in time that is polynomial in bothmand n.

Original languageAmerican English
Article number2835172
JournalJournal of the ACM
Volume63
Issue number2
DOIs
StatePublished - 7 Apr 2016

Bibliographical note

Publisher Copyright:
© 2016 ACM.

Keywords

  • Combinatorial auctions
  • Game theory
  • Mechanism design
  • Simultaneous item-bidding auctions

Fingerprint

Dive into the research topics of 'Bayesian combinatorial auctions'. Together they form a unique fingerprint.

Cite this