Prior-Independent Multi-parameter Mechanism Design

  • Nikhil Devanur
  • Jason Hartline
  • Anna Karlin
  • Thach Nguyen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7090)

Abstract

In a unit-demand multi-unit multi-item auction, an auctioneer is selling a collection of different items to a set of agents each interested in buying at most unit. Each agent has a different private value for each of the items. We consider the problem of designing a truthful auction that maximizes the auctioneer’s profit in this setting. Previously, there has been progress on this problem in the setting in which each value is drawn from a known prior distribution. Specifically, it has been shown how to design auctions tailored to these priors that achieve a constant factor approximation ratio [2, 5]. In this paper, we present a prior-independent auction for this setting. This auction is guaranteed to achieve a constant fraction of the optimal expected profit for a large class of, so called, “regular” distributions, without specific knowledge of the distributions.

Keywords

Price Auction Optimal Mechanism Favorite Item Supply Constraint Optimal Auction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nikhil Devanur
    • 1
  • Jason Hartline
    • 2
  • Anna Karlin
    • 3
  • Thach Nguyen
    • 3
  1. 1.Microsoft ResearchUSA
  2. 2.Northwestern UniversityUSA
  3. 3.University of WashingtonUSA

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