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95
Truthful Mechanisms for OneParameter Agents
"... In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s sec ..."
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Cited by 186 (4 self)
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In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s secret data is the cost she incurs per unit load. We give an exact characterization for the algorithms that can be used to design truthful mechanisms for such load balancing problems using appropriate side payments. We use our characterization to design polynomial time truthful mechanisms for several problems in combinatorial optimization to which the celebrated VCG mechanism does not apply. For scheduling related parallel machines (QjjCmax), we give a 3approximation mechanism based on randomized rounding of the optimal fractional solution. This problem is NPcomplete, and the standard approximation algorithms (greedy loadbalancing or the PTAS) cannot be used in truthful mechanisms. We show our mechanism to be frugal, in that the total payment needed is only a logarithmic factor more than the actual costs incurred by the machines, unless one machine dominates the total processing power. We also give truthful mechanisms for maximum flow, Qjj P Cj (scheduling related machines to minimize the sum of completion times), optimizing an affine function over a fixed set, and special cases of uncapacitated facility location. In addition, for Qjj P wjCj (minimizing the weighted sum of completion times), we prove a lower bound of 2 p 3 for the best approximation ratio achievable by a truthful mechanism.
Frugal path mechanisms
, 2002
"... We consider the problem of selecting a low cost s − t path in a graph, where the edge costs are a secret known only to the various economic agents who own them. To solve this problem, Nisan and Ronen applied the celebrated VickreyClarkeGroves (VCG) mechanism, which pays a premium to induce the edg ..."
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Cited by 108 (2 self)
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We consider the problem of selecting a low cost s − t path in a graph, where the edge costs are a secret known only to the various economic agents who own them. To solve this problem, Nisan and Ronen applied the celebrated VickreyClarkeGroves (VCG) mechanism, which pays a premium to induce the edges to reveal their costs truthfully. We observe that this premium can be unacceptably high. There are simple instances where the mechanism pays Θ(k) times the actual cost of the path, even if there is an alternate path available that costs only (1 + ɛ) times as much. This inspires the frugal path problem, which is to design a mechanism that selects a path and induces truthful cost revelation without paying such a high premium. This paper contributes negative results on the frugal path problem. On two large classes of graphs, including ones having three nodedisjoint s − t paths, we prove that no reasonable mechanism can always avoid paying a high premium to induce truthtelling. In particular, we introduce a general class of min function mechanisms, and show that all min function mechanisms can be forced to overpay just as badly as VCG. On the other hand, we prove that (on two large classes of graphs) every truthful mechanism satisfying some reasonable properties is a min function mechanism. 1
Mechanism design via differential privacy
 Proceedings of the 48th Annual Symposium on Foundations of Computer Science
, 2007
"... We study the role that privacypreserving algorithms, which prevent the leakage of specific information about participants, can play in the design of mechanisms for strategic agents, which must encourage players to honestly report information. Specifically, we show that the recent notion of differen ..."
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Cited by 106 (3 self)
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We study the role that privacypreserving algorithms, which prevent the leakage of specific information about participants, can play in the design of mechanisms for strategic agents, which must encourage players to honestly report information. Specifically, we show that the recent notion of differential privacy [15, 14], in addition to its own intrinsic virtue, can ensure that participants have limited effect on the outcome of the mechanism, and as a consequence have limited incentive to lie. More precisely, mechanisms with differential privacy are approximate dominant strategy under arbitrary player utility functions, are automatically resilient to coalitions, and easily allow repeatability. We study several special cases of the unlimited supply auction problem, providing new results for digital goods auctions, attribute auctions, and auctions with arbitrary structural constraints on the prices. As an important prelude to developing a privacypreserving auction mechanism, we introduce and study a generalization of previous privacy work that accommodates the high sensitivity of the auction setting, where a single participant may dramatically alter the optimal fixed price, and a slight change in the offered price may take the revenue from optimal to zero. 1
Competitive Generalized Auctions
, 2002
"... We describe mechanisms for auctions that are simultaneously truthful (alternately known as strategyproof or incentivecompatible) and guarantee high "net" profit. We make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. Thus, we do not req ..."
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Cited by 88 (19 self)
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We describe mechanisms for auctions that are simultaneously truthful (alternately known as strategyproof or incentivecompatible) and guarantee high "net" profit. We make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. Thus, we do not require any probabilistic assumptions on bids. We present
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 80 (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.
Multiunit auctions with budgetconstrained bidders
 In Proceedings of the 7th ACM Conference on Electronic Commerce
, 2005
"... We study a multiunit auction with multiple bidders, each of whom has a private valuation and a budget. The truthful mechanisms of such an auction are characterized, in the sense that, under standard assumptions, we prove that it is impossible to design a nontrivial truthful auction which allocates ..."
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Cited by 74 (10 self)
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We study a multiunit auction with multiple bidders, each of whom has a private valuation and a budget. The truthful mechanisms of such an auction are characterized, in the sense that, under standard assumptions, we prove that it is impossible to design a nontrivial truthful auction which allocates all units, while we provide the design of an asymptotically revenuemaximizing truthful mechanism which may allocate only some of the units. Our asymptotic parameter is a budget dominance parameter which measures the size of the budget of a single agent relative to the maximum revenue. We discuss the relevance of these results for the design of Internet ad auctions.
Approximation Algorithms and Online Mechanisms for Item Pricing
 IN ACM CONFERENCE ON ELECTRONIC COMMERCE
, 2005
"... We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller's revenue in an unlimited supply setting. Our first result is an O(k)approximation algorithm for pricing items to singleminded bidders who each want at most k items. This impr ..."
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Cited by 60 (9 self)
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We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller's revenue in an unlimited supply setting. Our first result is an O(k)approximation algorithm for pricing items to singleminded bidders who each want at most k items. This improves over recent independent work of Briest and Krysta [6] who achieve an O(k ) bound. For the case k = 2, where we obtain a 4approximation, this can be viewed as the following graph vertex pricing problem: given a (multi) graph G with valuations w e on the edges, find prices p i 0 for the vertices to maximize (p i + p j ) .
Frugality in Path Auctions
 In Proceedings of the 15th Annual ACMSIAM Symposium on Discrete Algorithms
, 2003
"... We consider the problem of picking (buying) an inexpensive s t path in a graph where edges are owned by independent (selfish) agents, and the cost of an edge is known to its owner only. We study the problem of finding frugal mechanisms for this task, i.e. we investigate the payments the buyer m ..."
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Cited by 59 (2 self)
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We consider the problem of picking (buying) an inexpensive s t path in a graph where edges are owned by independent (selfish) agents, and the cost of an edge is known to its owner only. We study the problem of finding frugal mechanisms for this task, i.e. we investigate the payments the buyer must make in order to buy a path.
Online Learning in Online Auctions
, 2003
"... ding truthfully and setting b i = v i . As shown in that paper, this condition # Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, Email: avrim@cs.cmu.edu + Strategic Planning and Optimization Team, Amazon.com, Seattle, WA, Email: vijayk@amazon.com # Department of Compute ..."
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Cited by 59 (5 self)
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ding truthfully and setting b i = v i . As shown in that paper, this condition # Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, Email: avrim@cs.cmu.edu + Strategic Planning and Optimization Team, Amazon.com, Seattle, WA, Email: vijayk@amazon.com # Department of Computer Science, University of Texas at Austin, Austin, TX. This work was done while the author was at IBM India Research Lab, New Delhi, India. Email: atri@cs.utexas.edu Computer Science Division, University of California at Berkeley, Berkeley, CA, Email: felix@cs.berkeley.edu is equivalent to the condition that each s i depends only on the first i 1 bids, and not on the ith bid. Hence, the auction mechanism is essentially trying to guess the ith valuation, based on the first i 1 valuations. As in previous papers [3, 5, 6], we will use competitive analysis to analyze the performance of any given auction. Hence, we are interested in the worstcase ratio (over all sequences of valuations)