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131
Winner determination in combinatorial auction generalizations
, 2002
"... Combinatorial markets where bids can be submitted on bundles of items can be economically desirable coordination mechanisms in multiagent systems where the items exhibit complementarity and substitutability. There has been a surge of recent research on winner determination in combinatorial auctions. ..."
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Cited by 165 (24 self)
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Combinatorial markets where bids can be submitted on bundles of items can be economically desirable coordination mechanisms in multiagent systems where the items exhibit complementarity and substitutability. There has been a surge of recent research on winner determination in combinatorial auctions. In this paper we study a wider range of combinatorial market designs: auctions, reverse auctions, and exchanges, with one or multiple units of each item, with and without free disposal. We first theoretically characterize the complexity. The most interesting results are that reverse auctions with free disposal can be approximated, and in all of the cases without free disposal, even finding a feasible solution is ÆÈcomplete. We then ran experiments on known benchmarks as well as ones which we introduced, to study the complexity of the market variants in practice. Cases with free disposal tended to be easier than ones without. On many distributions, reverse auctions with free disposal were easier than auctions with free disposal— as the approximability would suggest—but interestingly, on one of the most realistic distributions they were harder. Singleunit exchanges were easy, but multiunit exchanges were extremely hard. 1
The communication requirements of efficient allocations and supporting prices
 Journal of Economic Theory
, 2006
"... We show that any communication finding a Pareto efficient allocation in a privateinformation economy must also discover supporting Lindahl prices. In particular, efficient allocation of L indivisible objects requires naming a price for each of the 2 L ¡1 bundles. Furthermore, exponential communicat ..."
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Cited by 124 (16 self)
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We show that any communication finding a Pareto efficient allocation in a privateinformation economy must also discover supporting Lindahl prices. In particular, efficient allocation of L indivisible objects requires naming a price for each of the 2 L ¡1 bundles. Furthermore, exponential communication in L is needed just to ensure a higher share of surplus than that realized by auctioning all items as a bundle, or even a higher expected surplus (for some probability distribution over valuations). When the valuations are submodular, efficiency still requires exponential communication (and fully polynomial approximation is impossible). When the objects are homogeneous, arbitrarily good approximation is obtained using exponentially less communication than that needed for exact efficiency.
eMediator: A Next Generation Electronic Commerce Server
 Computational Intelligence
, 2002
"... This paper presents eMediator, an electronic commerce server prototype that demonstrates ways in which algorithmic support and gametheoretic incentive engineering can jointly improve the efficiency of ecommerce. eAuctionHouse, the configurable auction server, includes a variety of generalized combi ..."
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Cited by 115 (31 self)
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This paper presents eMediator, an electronic commerce server prototype that demonstrates ways in which algorithmic support and gametheoretic incentive engineering can jointly improve the efficiency of ecommerce. eAuctionHouse, the configurable auction server, includes a variety of generalized combinatorial auctions and exchanges, pricing schemes, bidding languages, mobile agents, and user support for choosing an auction type. We introduce two new logical bidding languages for combinatorial markets: the XOR bidding language and the ORofXORs bidding language. Unlike the traditional OR bidding language, these are fully expressive. They therefore enable the use of the ClarkeGroves pricing mechanism for motivating the bidders to bid truthfully. eAuctionHouse also supports supply/demand curve bidding. eCommitter, the leveled commitment contract optimizer, determines the optimal contract price and decommitting penalties for a variety of leveled commitment contracting mechanisms, taking into account that rational agents will decommit strategically in Nash equilibrium. It also determines the optimal decommitting strategies for any given leveled commitment contract. eExchangeHouse, the safe exchange planner, enables unenforced anonymous exchanges by dividing the exchange into chunks and sequencing those chunks to be delivered safely in alternation between the buyer and the seller.
Preference Elicitation in Combinatorial Auctions (Extended Abstract)
 IN PROCEEDINGS OF THE ACM CONFERENCE ON ELECTRONIC COMMERCE (ACMEC
, 2001
"... Combinatorial auctions (CAs) where bidders can bid on bundles of items can be very desirable market mechanisms when the items sold exhibit complementarity and/or substitutability, so the bidder's valuations for bundles are not additive. However, in a basic CA, the bidders may need to bid on e ..."
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Cited by 103 (29 self)
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Combinatorial auctions (CAs) where bidders can bid on bundles of items can be very desirable market mechanisms when the items sold exhibit complementarity and/or substitutability, so the bidder's valuations for bundles are not additive. However, in a basic CA, the bidders may need to bid on exponentially many bundles, leading to di#culties in determining those valuations, undesirable information revelation, and unnecessary communication. In this paper we present a design of an auctioneer agent that uses topological structure inherent in the problem to reduce the amount of information that it needs from the bidders. An analysis tool is presented as well as data structures for storing and optimally assimilating the information received from the bidders. Using this information, the agent then narrows down the set of desirable (welfaremaximizing or Paretoe#cient) allocations, and decides which questions to ask next. Several algorithms are presented that ask the bidders for value, order, and rank information. A method is presented for making the elicitor incentive compatible.
Truthful approximation mechanisms for restricted combinatorial auctions
, 2002
"... When attempting to design a truthful mechanism for a computationally hard problem such as combinatorial auctions, one is faced with the problem that most efficiently computable heuristics can not be embedded in any truthful mechanism (e.g. VCGlike payment rules will not ensure truthfulness). We dev ..."
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Cited by 103 (4 self)
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When attempting to design a truthful mechanism for a computationally hard problem such as combinatorial auctions, one is faced with the problem that most efficiently computable heuristics can not be embedded in any truthful mechanism (e.g. VCGlike payment rules will not ensure truthfulness). We develop a set of techniques that allow constructing efficiently computable truthful mechanisms for combinatorial auctions in the special case where each bidder desires a specific known subset of items and only the valuation is unknown by the mechanism (the single parameter case). For this case we extend the work of Lehmann O’Callaghan, and Shoham, who presented greedy heuristics. We show how to use IFTHENELSE constructs, perform a partial search, and use the LP relaxation. We apply these techniques for several canonical types of combinatorial auctions, obtaining truthful mechanisms with provable approximation ratios. 1
A New and Improved Design for MultiObject Iterative Auctions
 Management Science
, 2002
"... In this paper we present a new improved design for multiobject auctions and report on the results of experimental tests of that design. We merge the better features of two extant but very di#erent auction processes, the Simultaneous Multiple Round (SMR) design used by the FCC to auction spectrum ..."
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Cited by 102 (5 self)
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In this paper we present a new improved design for multiobject auctions and report on the results of experimental tests of that design. We merge the better features of two extant but very di#erent auction processes, the Simultaneous Multiple Round (SMR) design used by the FCC to auction spectrum and the Adaptive User Selection Mechanism (AUSM) of Banks, Ledyard, and Porter (1989). Then, by adding one crucial new feature, we are able to create a new design, the Resource Allocation Design (RAD) auction process, which performs better than both. Our experiments demonstrate, in both simple and complex environments, that the RAD auction achieves higher e#ciencies, lower bidder losses, and faster times to completion without increasing the complexity of a bidder's problem.
Achieving BudgetBalance with VickreyBased Payment Schemes in Exchanges
 In Proceedings of the 17th International Joint Conference on Artificial Intelligence
, 2001
"... Generalized Vickrey mechanisms have received wide attention in the literature because they are efficient and strategyproof, i.e. truthful bidding is optimal whatever the bids of other agents. However it is wellknown that it is impossible for an exchange, with multiple buyers and sellers, to be ..."
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Cited by 100 (18 self)
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Generalized Vickrey mechanisms have received wide attention in the literature because they are efficient and strategyproof, i.e. truthful bidding is optimal whatever the bids of other agents. However it is wellknown that it is impossible for an exchange, with multiple buyers and sellers, to be efficient and budgetbalanced, even putting strategyproofness to one side. A marketmaker in an efficient exchange must make more payments than it collects. We enforce budgetbalance as a hard constraint, and explore payment rules to distribute surplus after an exchange clears to minimize distance to Vickrey payments. Different rules lead to different levels of truthrevelation and efficiency. Experimental and theoretical analysis suggest a simple Threshold scheme, which gives surplus to agents with payments further than a certain threshold value from their Vickrey payments. The scheme appears able to exploit agent uncertainty about bids from other agents to reduce manipulation and boost allocative efficiency in comparison with other simple rules.
Vickrey Prices and Shortest Paths: What is an edge worth?
 In Proceedings of the 42nd Symposium on the Foundations of Computer Science, IEEE Computer Society Press, Los Alamitos
, 2001
"... We solve a shortest path problem that is motivated by recent interest in pricing networks or other computational resources. Informally, how much is an edge in a network worth to a user who wants to send data between two nodes along a shortest path? If the network is a decentralized entity, such as t ..."
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Cited by 93 (5 self)
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We solve a shortest path problem that is motivated by recent interest in pricing networks or other computational resources. Informally, how much is an edge in a network worth to a user who wants to send data between two nodes along a shortest path? If the network is a decentralized entity, such as the Internet, in which multiple selfinterested agents own different parts of the network, then auctionbased pricing seems appropriate. A celebrated result from auction theory shows that the use of Vickrey pricing motivates the owners of the network resources to bid truthfully. In Vickrey's scheme, each agent is compensated in proportion to the marginal utility he brings to the auction. In the context of shortest path routing, an edge's utility is the value by which it lowers the length of the shortest paththe difference between the shortest path lengths with and without the edge. Our problem is to compute these marginal values for all the edges of the network efficiently. The na ve method requires solving the singlesource shortest path problem up to n times, for an nnode network. We show that the Vickrey prices for all the edges can be computed in the same asymptotic time complexity as one singlesource shortest path problem. This solves an open problem posed by Nisan and Ronen [12]. 1.
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 66 (20 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.
Costly valuation computation in auctions
 IN IN PROCEEDINGS OF THE EIGHTH CONFERENCE OF THEORETICAL ASPECTS OF KNOWLEDGE AND RATIONALITY (TARK VIII), SIENNA
, 2001
"... We investigate deliberation and bidding strategies of agents with unlimited but costly computation who are participating in auctions. The agents do not a priori know their valuations for the items begin auctioned. Instead they devote computational resources to compute their valuations. We present a ..."
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Cited by 57 (27 self)
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We investigate deliberation and bidding strategies of agents with unlimited but costly computation who are participating in auctions. The agents do not a priori know their valuations for the items begin auctioned. Instead they devote computational resources to compute their valuations. We present a normative model of bounded rationality where deliberation actions of agents are incorporated into strategies and equilibria are analyzed for standard auction protocols. We show that even in settings such as English auctions where information about other agents ’ valuations is revealed for free by the bidding process, agents may still compute on opponents’ valuation problems, incurring a cost, in order to determine how to bid. We compare the costly computation model of bounded rationality with a different model where computation is free but limited. For some auction mechanisms the equilibrium strategies are substantially different. It can be concluded that the model of bounded rationality impacts the agents’ equilibrium strategies and must be considered when designing mechanisms for computationally limited agents.