Results 11  20
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458
ApproximatelyStrategyproof and Tractable MultiUnit Auctions
, 2004
"... We present an approximatelyefficient and approximatelystrategyproof auction mechanism for a singlegood multiunit allocation problem. The bidding language allows marginaldecreasing piecewise constant curves and quantitybased side constraints. We develop a fully polynomialtime approximation sch ..."
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Cited by 61 (11 self)
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We present an approximatelyefficient and approximatelystrategyproof auction mechanism for a singlegood multiunit allocation problem. The bidding language allows marginaldecreasing piecewise constant curves and quantitybased side constraints. We develop a fully polynomialtime approximation scheme for the multiunit allocation problem, which computes a approximation in worstcase time , given bids each with a constant number of pieces. We integrate this approximation scheme within a VickreyClarke Groves mechanism and compute payments for an asymptotic cost of ! . The maximal possible gain from manipulation to a bidder in the combined scheme is bounded by 429416716 " is the total surplus in the efficient outcome.
An inverseoptimizationbased auction mechanism to support a multiattribute RFQ process
, 2001
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On Ascending Vickrey Auctions for Heterogeneous Objects
, 2005
"... We construct an ascending auction for heterogeneous objects by applying a primaldual algorithm to a linear program that represents the efficientallocation problem for this setting. The auction assigns personalized prices to bundles, and asks bidders to report their preferred bundles in each round. ..."
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Cited by 53 (4 self)
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We construct an ascending auction for heterogeneous objects by applying a primaldual algorithm to a linear program that represents the efficientallocation problem for this setting. The auction assigns personalized prices to bundles, and asks bidders to report their preferred bundles in each round. A bidder’s prices are increased when he belongs to a “minimally undersupplied ” set of bidders. This concept generalizes the notion of “overdemanded” sets of objects introduced by Demange et al. (1986) for the onetoone assignment problem. Under a submodularity condition, the auction implements the Vickrey–Clarke–Groves outcome; we show that this type of condition is somewhat necessary to do so. When classifying the ascendingauction literature in terms of their underlying algorithms, our auction fills a gap in that literature. We relate our results to various ascending auctions in the literature.
Auctions with Severely Bounded Communication
 In Proceedings of the 43rd Annual Symposium on Foundations of Computer Science (FOCS 02
, 2002
"... We study auctions with severe bounds on the communication allowed: each bidder may only transmit t bits of information to the auctioneer. We consider both welfaremaximizing and revenuemaximizing auctions under this communication restriction. For both measures, we determine the optimal auction an ..."
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Cited by 53 (9 self)
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We study auctions with severe bounds on the communication allowed: each bidder may only transmit t bits of information to the auctioneer. We consider both welfaremaximizing and revenuemaximizing auctions under this communication restriction. For both measures, we determine the optimal auction and show that the loss incurred relative to unconstrained auctions is mild. We prove nonsurprising properties of these kinds of auctions, e.g. that discrete prices are informationally ecient, as well as some surprising properties, e.g. that asymmetric auctions are better than symmetric ones.
Inapproximability results for combinatorial auctions with submodular utility functions
 in Proceedings of WINE 2005
, 2005
"... We consider the following allocation problem arising in the setting of combinatorial auctions: a set of goods is to be allocated to a set of players so as to maximize the sum of the utilities of the players (i.e., the social welfare). In the case when the utility of each player is a monotone submodu ..."
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Cited by 49 (0 self)
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We consider the following allocation problem arising in the setting of combinatorial auctions: a set of goods is to be allocated to a set of players so as to maximize the sum of the utilities of the players (i.e., the social welfare). In the case when the utility of each player is a monotone submodular function, we prove that there is no polynomial time approximation algorithm which approximates the maximum social welfare by a factor better than 1 − 1/e � 0.632, unless P = NP. Our result is based on a reduction from a multiprover proof system for MAX3COLORING. 1
Mdpop: Faithful distributed implementation of efficient social choice problems
 In AAMAS’06  Autonomous Agents and Multiagent Systems
, 2006
"... In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem ..."
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Cited by 48 (17 self)
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In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem as a distributed constraint optimization problem (DCOP), in which each agent can communicate with other agents that share an interest in one or more variables. Whereas existing DCOP algorithms can be easily manipulated by an agent, either by misreporting private information or deviating from the algorithm, we introduce MDPOP, the first DCOP algorithm that provides a faithful distributed implementation for efficient social choice. This provides a concrete example of how the methods of mechanism design can be unified with those of distributed optimization. Faithfulness ensures that no agent can benefit by unilaterally deviating from any aspect of the protocol, neither informationrevelation, computation, nor communication, and whatever the private information of other agents. We allow for payments by agents to a central bank, which is the only central authority that we require. To achieve faithfulness, we carefully integrate the VickreyClarkeGroves (VCG) mechanism with the DPOP algorithm, such that each agent is only asked to perform computation, report
Efficiency and envyfreeness in fair division of indivisible goods: Logical representation and complexity
 In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI2005
, 2005
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Negotiating socially optimal allocations of resources
 2006) 315–348. P.E. Dunne, Y. Chevaleyre / Theoretical Computer Science 396
, 2008
"... A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then ana ..."
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Cited by 47 (20 self)
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A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually. 1.
Item Pricing for Revenue Maximization
"... We consider the problem of pricing n items to maximize revenue when faced with a series of unknown buyers with complex preferences, and show that a simple pricing scheme achieves surprisingly strong guarantees. We show that in the unlimited supply setting, a random single price achieves expected rev ..."
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Cited by 41 (4 self)
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We consider the problem of pricing n items to maximize revenue when faced with a series of unknown buyers with complex preferences, and show that a simple pricing scheme achieves surprisingly strong guarantees. We show that in the unlimited supply setting, a random single price achieves expected revenue within a logarithmic factor of the total social welfare for customers with general valuation functions, which may not even necessarily be monotone. This generalizes work of Guruswami et. al [18], who show a logarithmic factor for only the special cases of singleminded and unitdemand customers. In the limited supply setting, we show that for subadditive valuations, a random single price achieves revenue within a factor of 2 O( √ log n log log n) of the total social welfare, i.e., the optimal revenue the seller could hope to extract even if the seller could price each bundle differently for every buyer. This is the best approximation known for any item pricing scheme for subadditive (or even submodular) valuations, even using multiple prices. We complement this result with a lower bound showing a sequence of subadditive (in fact, XOS) buyers for which any single price has approximation ratio 2 Ω(log1/4 n), thus showing that single price schemes cannot achieve a polylogarithmic ratio. This lower bound demonstrates a clear distinction between revenue maximization and social welfare maximization in this setting, for which [12, 10] show that a fixed price achieves a logarithmic approximation in the case of XOS [12], and more generally subadditive [10], customers.