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59
Competitive Auctions
, 2002
"... We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of ..."
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Cited by 83 (10 self)
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We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of the profit of optimal fixed pricing for all inputs. We justify the use of optimal fixed pricing as a benchmark for evaluating competitive auction profit. We show that several randomized auctions are truthful and competitive and that no truthful deterministic auction is competitive. Our results extend to bounded supply markets, for which we also get truthful and competitive auctions.
Knapsack Auctions
 Proceedings of the Seventeenth Annual ACMSIAM Symposium on Discrete Algorithms (SODA
, 2006
"... We consider a game theoretic knapsack problem that has application to auctions for selling advertisements on Internet search engines. Consider n agents each wishing to place an object in the knapsack. Each agent has a private valuation for having their object in the knapsack and each object has a pu ..."
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Cited by 61 (12 self)
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We consider a game theoretic knapsack problem that has application to auctions for selling advertisements on Internet search engines. Consider n agents each wishing to place an object in the knapsack. Each agent has a private valuation for having their object in the knapsack and each object has a publicly known size. For this setting, we consider the design of auctions in which agents have an incentive to truthfully reveal their private valuations. Following the framework of Goldberg et al. [10], we look to design an auction that obtains a constant fraction of the profit obtainable by a natural optimal pricing algorithm that knows the agents ’ valuations and object sizes. We give an auction that obtains a constant factor approximation in the nontrivial special case where the knapsack has unlimited capacity. We then reduce the limited capacity version of the problem to the unlimited capacity version via an approximately efficient auction (i.e., one that maximizes the social welfare). This reduction follows from generalizable principles. 1
Online Decision Problems with Large Strategy Sets
, 2005
"... In an online decision problem, an algorithm performs a sequence of trials, each of which involves selecting one element from a fixed set of alternatives (the “strategy set”) whose costs vary over time. After T trials, the combined cost of the algorithm’s choices is compared with that of the single s ..."
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Cited by 26 (2 self)
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In an online decision problem, an algorithm performs a sequence of trials, each of which involves selecting one element from a fixed set of alternatives (the “strategy set”) whose costs vary over time. After T trials, the combined cost of the algorithm’s choices is compared with that of the single strategy whose combined cost is minimum. Their difference is called regret, and one seeks algorithms which are efficient in that their regret is sublinear in T and polynomial in the problem size. We study an important class of online decision problems called generalized multiarmed bandit problems. In the past such problems have found applications in areas as diverse as statistics, computer science, economic theory, and medical decisionmaking. Most existing algorithms were efficient only in the case of a small (i.e. polynomialsized) strategy set. We extend the theory by supplying nontrivial algorithms and lower bounds for cases in which the strategy set is much larger (exponential or infinite) and
From Optimal Limited to Unlimited Supply Auctions
 In EC
, 2005
"... We investigate the class of singleround, sealedbid auctions for a set of identical items to bidders who each desire one unit. We adopt the worstcase competitive framework defined by [9, 5] that compares the profit of an auction to that of an optimal singleprice sale of least two items. In this p ..."
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Cited by 26 (7 self)
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We investigate the class of singleround, sealedbid auctions for a set of identical items to bidders who each desire one unit. We adopt the worstcase competitive framework defined by [9, 5] that compares the profit of an auction to that of an optimal singleprice sale of least two items. In this paper, we first derive an optimal auction for three items, answering an open question from [8]. Second, we show that the form of this auction is independent of the competitive framework used. Third, we propose a schema for converting a given limitedsupply auction into an unlimited supply auction. Applying this technique to our optimal auction for three items, we achieve an auction with a competitive ratio of 3.25, which improves upon the previously bestknown competitive ratio of 3.39 from [7]. Finally, we generalize a result from [8] and extend our understanding of the nature of the optimal competitive auction by showing that the optimal competitive auction occasionally offers prices that are higher than all bid values.
Competitiveness via Consensus
, 2002
"... We introduce Consensus Revenue Estimate (CORE) auctions. This is a class of competitive auctions that is interesting for several reasons. One auction from this class achieves a better competitive ratio than any previously known auction. Another one uses only two random bits, whereas the previously k ..."
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Cited by 24 (8 self)
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We introduce Consensus Revenue Estimate (CORE) auctions. This is a class of competitive auctions that is interesting for several reasons. One auction from this class achieves a better competitive ratio than any previously known auction. Another one uses only two random bits, whereas the previously known competitive auctions on n bidders use n random bits. A parameterized CORE auction performs better than the previous auctions in the context of massmarket goods, such as digital goods. The improved performance is due to the consensus estimate technique that allows more information to be extracted from the input. This technique is very natural and may be useful in other contexts.
Market research and market design
 Advances in Theoretical Economics
, 2003
"... be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher, bepress. Advances in Theoretical Economics is one of The B.E. ..."
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Cited by 21 (0 self)
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be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher, bepress. Advances in Theoretical Economics is one of The B.E.
On the Competitive Ratio of the Random Sampling Auction
 In Proc. 1st Workshop on Internet and Network Economics
, 2005
"... Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture ..."
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Cited by 19 (6 self)
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Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture that random sampling auction is in fact 4competitive, we show that on the equal revenue input, where any sale price gives the same revenue, random sampling is exactly a factor of four from optimal. 1 Introduction. Random sampling is the most prevalent technique for designing auctions to maximize the auctioneer’s profit when the bidders ’ valuations are a priori unknown [2–4, 7, 8, 10, 11]. The first and simplest application of random sampling to auctions is in the context of auctioning a digital good. 5 For this problem, the random
Foundations of Dominant Strategy Mechanisms
 REVIEW OF ECONOMIC STUDIES
, 2004
"... Wilson (1987) criticizes the existing literature of game theory as relying too much on commonknowledge assumptions. In reaction to Wilson’s critique, the recent literature of mechanism design has started employing simpler mechanisms such as dominant strategy mechanisms. However, there has been litt ..."
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Cited by 14 (0 self)
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Wilson (1987) criticizes the existing literature of game theory as relying too much on commonknowledge assumptions. In reaction to Wilson’s critique, the recent literature of mechanism design has started employing simpler mechanisms such as dominant strategy mechanisms. However, there has been little theory behind this approach. In particular, it has not been made clear why, when a mechanism designer is not willing to make strong commonknowledge assumptions, she would respond by using simpler mechanisms instead of even more complicated ones. This paper tries to fill the void and investigates some foundations for using simpler mechanisms such as dominant strategy mechanisms.
Information in Mechanism Design
 IN ADVANCES IN ECONOMICS AND ECONOMETRICS
, 2006
"... We survey the recent literature on the role of information in mechanism design. First, we discuss an emerging literature on the role of endogenous payo and strategic information for the design and the efficiency of the mechanism. We speci cally consider information management in the form of acquisit ..."
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Cited by 13 (2 self)
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We survey the recent literature on the role of information in mechanism design. First, we discuss an emerging literature on the role of endogenous payo and strategic information for the design and the efficiency of the mechanism. We speci cally consider information management in the form of acquisition of new information or disclosure of existing information. Second, we argue that in the presence of endogenous information, the robustness of the mechanism to the type space and higher order beliefs becomes a natural desideratum. We discuss recent approaches to robust mechanism design and robust implementation.
A Lower Bound on the Competitive Ratio of Truthful Auctions
 In Proceedings 21st Symposium on Theoretical Aspects of Computer Science
, 2004
"... Abstract We study a class of singleround, sealedbid auctions for a set of identical items. We adopt the worst case competitive framework defined by [1,2] that compares the profit of an auction to that of an optimal single price sale to at least two bidders. In this framework, we give a lower bound ..."
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Cited by 11 (5 self)
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Abstract We study a class of singleround, sealedbid auctions for a set of identical items. We adopt the worst case competitive framework defined by [1,2] that compares the profit of an auction to that of an optimal single price sale to at least two bidders. In this framework, we give a lower bound of 2.42 (an improvement from the bound of 2 given in [2]) on the competitive ratio of any truthful auction, one where each bidders best strategy is to declare the true maximum value an item is worth to them. This result contrasts with the 3.39 competitive ratio of the best known truthful auction [3]. 1