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275
Incentive compatible multi unit combinatorial auctions
 In TARK 03
, 2003
"... This paper deals with multiunit combinatorial auctions where there are n types of goods for sale, and for each good there is some fixed number of units. We focus on the case where each bidder desires a relatively small number of units of each good. In particular, this includes the case where each g ..."
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Cited by 112 (13 self)
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This paper deals with multiunit combinatorial auctions where there are n types of goods for sale, and for each good there is some fixed number of units. We focus on the case where each bidder desires a relatively small number of units of each good. In particular, this includes the case where each good has exactly k units, and each bidder desires no more than a single unit of each good. We provide incentive compatible mechanisms for combinatorial auctions for the general case where bidders are not limited to single minded valuations. The mechanisms we give have approximation ratios close to the best possible for both online and offline scenarios. This is the first result where nonVCG mechanisms are derived for nonsingle minded bidders for a natural model of combinatorial auctions.
Bidding languages for combinatorial auctions
 In Proc. 17th Intl. Joint Conference on Artif. Intell
, 2001
"... Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bi ..."
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Cited by 98 (1 self)
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Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bidding languages allow the expression of complex utility functions in a natural and concise way. We introduce a new, generalized language where bids are given by propositional formulae whose subformulae can be annotated with prices. This language allows bidder utilities to be formulated more naturally and concisely than existing languages. Furthermore, we outline a general algorithmic technique for winner determination for auctions that use this bidding language. 1
Logical preference representation and combinatorial vote,
 Annals of Mathematics and Artificial Intelligence
, 2004
"... We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of nonindependent variables to assign. We study two key issues pertaining to combinatorial vote, namely preference representation and ..."
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Cited by 96 (16 self)
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We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of nonindependent variables to assign. We study two key issues pertaining to combinatorial vote, namely preference representation and the automated choice of an optimal decision. For each of these issues, we briefly review the state of the art, we try to define the main problems to be solved and identify their computational complexity.
Approximation Techniques for Utilitarian Mechanism Design
, 2005
"... This paper deals with the design of efficiently computable incentive compatible, or truthful, mechanisms for combinatorial optimization problems with multiparameter agents. We focus on approximation algorithms for NPhard mechanism design problems. These algorithms need to satisfy certain monotonic ..."
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Cited by 92 (5 self)
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This paper deals with the design of efficiently computable incentive compatible, or truthful, mechanisms for combinatorial optimization problems with multiparameter agents. We focus on approximation algorithms for NPhard mechanism design problems. These algorithms need to satisfy certain monotonicity properties to ensure truthfulness. Since most of the known approximation techniques do not fulfill these properties, we study alternative techniques. Our first contribution is a quite general method to transform a pseudopolynomial algorithm into a monotone FPTAS. This can be applied to various problems like, e.g., knapsack, constrained shortest path, or job scheduling with deadlines. For example, the monotone FPTAS for the knapsack problem gives a very efficient, truthful mechanism for singleminded multiunit auctions. The best previous result for such auctions was a 2approximation. In addition, we present a monotone PTAS for the generalized assignment problem with any bounded number of parameters per agent. The most efficient way to solve packing integer programs (PIPs) is LPbased randomized rounding, which also is in general not monotone. We show that primaldual greedy algorithms achieve almost the same approximation ratios for PIPs as randomized rounding. The advantage is that these algorithms are inherently monotone. This way, we can significantly improve the approximation ratios of truthful mechanisms for various fundamental mechanism design problems like singleminded combinatorial auctions (CAs), unsplittable flow routing and multicast routing. Our approximation algorithms can also be used for the winner determination in CAs with general bidders specifying their bids through an oracle.
Mirage: A Microeconomic Resource Allocation System for Sensornet Testbeds
 In Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors
, 2005
"... technical challenges of wireless SensorNets. As the size and demand for these testbeds grow, resource management will become increasingly important to the effectiveness of these environments. In this paper, we argue that a microeconomic resource allocation scheme, specifically the combinatorial auct ..."
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Cited by 78 (7 self)
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technical challenges of wireless SensorNets. As the size and demand for these testbeds grow, resource management will become increasingly important to the effectiveness of these environments. In this paper, we argue that a microeconomic resource allocation scheme, specifically the combinatorial auction, is well suited to testbed resource management. To demonstrate this, we present the Mirage resource allocation system. In Mirage, testbed resources are allocated using a repeated combinatorial auction within a closed virtual currency environment. Users compete for testbed resources by submitting bids which specify resource combinations of interest in space/time (e.g., "any 32 MICA2 motes for 8 hours anytime in the next three days") along with a maximum value amount the user is willing to pay. A combinatorial auction is then periodically run to determine the winning bids based on supply and demand while maximizing aggregate utility delivered to users. We have implemented a fully functional and secure prototype of Mirage and have been operating it in daily use for approximately two months on Intel Research Berkeley's 148mote SensorNet testbed.
Learning the Empirical Hardness of Optimization Problems: The case of combinatorial auctions
 In CP
, 2002
"... We propose a new approach to understanding the algorithmspecific empirical hardness of optimization problems. In this work we focus on the empirical hardness of the winner determination probleman optimization problem arising in combinatorial auctionswhen solved by ILOG's CPLEX software. ..."
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Cited by 78 (23 self)
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We propose a new approach to understanding the algorithmspecific empirical hardness of optimization problems. In this work we focus on the empirical hardness of the winner determination probleman optimization problem arising in combinatorial auctionswhen solved by ILOG's CPLEX software. We consider nine widelyused problem distributions and sample randomly from a continuum of parameter settings for each distribution. First, we contrast the overall empirical hardness of the different distributions. Second, we identify a large number of distributionnonspecific features of data instances and use statistical regression techniques to learn, evaluate and interpret a function from these features to the predicted hardness of an instance.
Optimal Solutions for MultiUnit Combinatorial Auctions: Branch and Bound Heuristics
 In Proceedings of the Second acm Conference on Electronic Commerce
, 2000
"... Finding optimal solutions for multiunit combinatorial auctions is a hard problem and nding approximations to the optimal solution is also hard. We investigate the use of BranchandBound techniques: they require both a way to bound from above the value of the best allocation and a good criterion to ..."
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Cited by 76 (4 self)
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Finding optimal solutions for multiunit combinatorial auctions is a hard problem and nding approximations to the optimal solution is also hard. We investigate the use of BranchandBound techniques: they require both a way to bound from above the value of the best allocation and a good criterion to decide which bids are to be tried rst. Dierent methods for eciently bounding from above the value of the best allocation are considered. Theoretical original results characterize the best approximation ratio and the ordering criterion that provides it. We suggest to use this criterion. Keywords Combinatorial Auctions, Branch and Bound 1. MULTIUNIT COMBINATORIAL AUCTIONS (MUCAS) Auctions have been used from times immemorial, but the renewed modern interest in auctions stems from: their increased use for selling o government property after WWII and later in extensive denationalizations, and the theoretical breakthroughs started by [14]. A very recent surge of interest in aucti...
AkBA: A Progressive, AnonymousPrice Combinatorial Auction
, 2000
"... The allocation of discrete, complementm'y resources is a fundamental probleln in econolnics and of direct interest to ecolnlnerce applications. Combinatorial auctions account for complementarities by optimizing over offers expressed in terms of bundles. Progressive versions of combinatorial au ..."
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Cited by 73 (7 self)
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The allocation of discrete, complementm'y resources is a fundamental probleln in econolnics and of direct interest to ecolnlnerce applications. Combinatorial auctions account for complementarities by optimizing over offers expressed in terms of bundles. Progressive versions of combinatorial auctions alleviate the burden on bidders of expressing offers for all bundles of interest by providing interiln feedback based on partial sets of bids. Feedback in terms of hypothetical prices is particularly useful, as it directs bidders to,yard those bundles potentially yielding the greatest surplus. For a general class of discrete resource allocation problelns vith free disposal, we establish by construction the existence of competitive equilibriuln prices on bundles that support the efficient allocation. We introduce AkBA, a falnily of progressive auctions that use these equilibriuln bundle prices. We exalnine a particular instance of the family, called A1BA, and present SOlne elnpirical data on its perforlnance.
Bundling Equilibrium in Combinatorial Auctions
, 2001
"... This paper analyzes individuallyrational ex post equilibrium in the VC (VickreyClarke) combinatorial auctions. If \Sigma is a family of bundles of goods, the organizer may restrict the participants by requiring them to submit their bids only for bundles in \Sigma. The \SigmaVC combinatorial aucti ..."
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Cited by 60 (10 self)
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This paper analyzes individuallyrational ex post equilibrium in the VC (VickreyClarke) combinatorial auctions. If \Sigma is a family of bundles of goods, the organizer may restrict the participants by requiring them to submit their bids only for bundles in \Sigma. The \SigmaVC combinatorial auctions (multigood auctions) obtained in this way are known to be individuallyrational truthtelling mechanisms. In contrast, this paper deals with nonrestricted VC auctions, in which the buyers restrict themselves to bids on bundles in \Sigma, because it is rational for them to do so. That is, it may be that when the buyers report their valuation of the bundles in \Sigma, they are in an equilibrium. We fully characterize those \Sigma that induce individually rational equilibrium in every VC auction, and we refer to the associated equilibrium as a bundling equilibrium. The number of bundles in \Sigma represents the communication complexity of the equilibrium. A special case of bundling equilibrium is partitionbased equilibrium, in which \Sigma is a field, that is, it is generated by a partition. We analyze the tradeoff between communication complexity and economic efficiency of bundling equilibrium, focusing in particular on partitionbased equilibrium.
Applying Learning Algorithms to Preference Elicitation in Combinatorial Auctions
, 2004
"... We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that learning algorithms can be used as a basis for preference elicitation algorithms. The resulting elicitation algorithms ..."
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Cited by 56 (14 self)
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We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that learning algorithms can be used as a basis for preference elicitation algorithms. The resulting elicitation algorithms perform a polynomial number of queries. We also give conditions under which the resulting algorithms have polynomial communication. Our conversion procedure allows us to generate combinatorial auction protocols from learning algorithms for polynomials, monotone DNF, and linearthreshold functions. In particular, we obtain an algorithm that elicits XOR bids with polynomial communication. We then characterize the communication requirements of implementing Vickrey payments with an elicitation algorithm. This suggests a modification to the queries in our elicitation algorithms so that truthful bidding becomes an expost Nash equilibrium.