The Value of Knowing Your Enemy

نویسندگان

  • Christos Tzamos
  • Christopher A. Wilkens
چکیده

Many auction settings implicitly or explicitly require that bidders are treated equally exante. This may be because discrimination is philosophically or legally impermissible, or because it is practically difficult to implement or impossible to enforce. We study so-called anonymous auctions to understand the revenue tradeoffs and to develop simple anonymous auctions that are approximately optimal. We consider digital goods settings and show that the optimal anonymous, dominant strategy incentive compatible auction has an intuitive structure — imagine that bidders are randomly permuted before the auction, then infer a posterior belief about bidder i’s valuation from the values of other bidders and set a posted price that maximizes revenue given this posterior. We prove that no anonymous mechanism can guarantee an approximation better than Θ(n) to the optimal revenue in the worst case (or Θ(logn) for regular distributions) and that even posted price mechanisms match those guarantees. Understanding that the real power of anonymous mechanisms comes when the auctioneer can infer the bidder identities accurately, we show a tight Θ(k) approximation guarantee when each bidder can be confused with at most k “higher types”. Moreover, we introduce a simple mechanism based on n target prices that is asymptotically optimal and build on this mechanism to extend our results to m-unit auctions and sponsored search. Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; [email protected]. Supported by NSF Award CCF-1101491. Parts of this work were done while the author was an intern at Yahoo Labs. Yahoo Labs, Sunnyvale, California, USA; [email protected].

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عنوان ژورنال:
  • CoRR

دوره abs/1411.1379  شماره 

صفحات  -

تاریخ انتشار 2014