Truthful randomized mechanisms for combinatorial auctions

Shahar Dobzinski*, Noam Nisan, Michael Schapira

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

We present a new framework for the design of computationally-efficient and incentive-compatible mechanisms for combinatorial auctions. The mechanisms obtained via this framework are randomized, and obtain incentive compatibility in the universal sense (in contrast to the substantially weaker notion of incentive compatibility in expectation). We demonstrate the usefulness of our techniques by exhibiting two mechanisms for combinatorial auctions with general bidder preferences. The first mechanism obtains an optimal O(m)-approximation to the optimal social welfare for arbitrary bidder valuations. The second mechanism obtains an O(log2m)-approximation for a class of bidder valuations that contains the important class of submodular bidders. These approximation ratios greatly improve over the best (known) deterministic incentive-compatible mechanisms for these classes.

Original languageAmerican English
Pages (from-to)15-25
Number of pages11
JournalJournal of Computer and System Sciences
Volume78
Issue number1
DOIs
StatePublished - Jan 2012

Bibliographical note

Funding Information:
We thank Moshe Babaioff, Liad Blumrosen, Uri Feige, Ron Lavi, Ahuva Mu’alem, and Chaitanya Swamy for helpful discussions and comments. The second author is supported by a grant from the Israeli Academy of Sciences. The third author is supported by NSF grant 0331548. The work was partially done when the first and third authors were in the Hebrew University and were supported by a grant from the Israeli Academy of Sciences. A preliminary version of this paper appeared in STOC’06.

Keywords

  • Approximation algorithms
  • Combinatorial auctions
  • Truthfulness

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