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157
Algorithmic mechanism design
 Games and Economic Behavior
, 1999
"... We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agen ..."
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Cited by 662 (23 self)
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We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agents ’ interests are best served by behaving correctly. Following notions from the field of mechanism design, we suggest a framework for studying such algorithms. Our main technical contribution concerns the study of a representative task scheduling problem for which the standard mechanism design tools do not suffice. Journal of Economic Literature
Bidding and Allocation in Combinatorial Auctions
 IN ACM CONFERENCE ON ELECTRONIC COMMERCE
, 2000
"... When an auction of multiple items is performed, it is often desirable to allow bids on combinations of items, as opposed to only on single items. Such an auction is often called "combinatorial", and the exponential number of possible combinations results in computational intractability o ..."
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Cited by 275 (11 self)
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When an auction of multiple items is performed, it is often desirable to allow bids on combinations of items, as opposed to only on single items. Such an auction is often called "combinatorial", and the exponential number of possible combinations results in computational intractability of many aspects regarding such an auction. This paper considers two of these aspects: the bidding language and the allocation algorithm. First we consider which kinds of bids on combinations are allowed and how, i.e. in what language, they are specified. The basic tradeoff is the expressibility of the language versus its simplicity. We consider and formalize several bidding languages and compare their strengths. We prove exponential separations between the expressive power of different languages, and show that one language, "ORbids with phantom items", can polynomially simulate the others. We then consider the problem of determining the best allocation  a problem known to be computationally intractable. We suggest an approach based on Linear Programming (LP) and motivate it. We prove that the LP approach finds an optimal allocation if and only if prices can be attached to single items in the auction. We pinpoint several classes of auctions where this is the case, and suggest greedy and branchandbound heuristics based on LP for other cases.
Privacy Preserving Auctions and Mechanism Design
, 1999
"... We suggest an architecture for executing protocols for auctions and, more generally, mechanism design. Our goal is to preserve the privacy of the inputs of the participants (so that no nonessential information about them is divulged, even a posteriori) while maintaining communication and computation ..."
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Cited by 247 (13 self)
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We suggest an architecture for executing protocols for auctions and, more generally, mechanism design. Our goal is to preserve the privacy of the inputs of the participants (so that no nonessential information about them is divulged, even a posteriori) while maintaining communication and computational efficiency. We achieve this goal by adding another party  the auction issuer  that generates the programs for computing the auctions but does not take an active part in the protocol. The auction issuer is not a trusted party, but is assumed not to collude with the auctioneer. In the case of auctions, barring collusion between the auctioneer and the auction issuer, neither party gains any information about the bids, even after the auction is over. Moreover, bidders can verify that the auction was performed correctly. The protocols do not require any communication between the bidders and the auction issuer and the computational efficiency is very reasonable. This architecture can be used to implement any mechanism design where the important factor is the complexity of the decision procedure.
Computationally feasible VCG mechanisms
 In Proceedings of the Second ACM Conference on Electronic Commerce (EC’00
, 2000
"... A major achievement of mechanism design theory is a general method for the construction of truthful mechanisms called VCG. When applying this method to complex problems such as combinatorial auctions, a difficulty arises: VCG mechanisms are required to compute optimal outcomes and are therefore comp ..."
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Cited by 216 (6 self)
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A major achievement of mechanism design theory is a general method for the construction of truthful mechanisms called VCG. When applying this method to complex problems such as combinatorial auctions, a difficulty arises: VCG mechanisms are required to compute optimal outcomes and are therefore computationally infeasible. However, if the optimal outcome is replaced by the results of a suboptimal algorithm, the resulting mechanism (termed VCGbased) is no longer necessarily truthful. The first part of this paper studies this phenomenon in depth and shows that it is near universal. Specifically, we prove that essentially all reasonable approximations or heuristics for combinatorial auctions as well as a wide class of cost minimization problems yield nontruthful VCGbased mechanisms. We generalize these results for affine maximizers. The second part of this paper proposes a general method for circumventing the above problem. We introduce a modification of VCGbased mechanisms in which the agents are given a chance to improve the output of the underlying algorithm. When the agents behave truthfully, the welfare obtained by the mechanism is at least as good as the one obtained by the algorithm’s output. We provide a strong rationale for truthtelling behavior. Our method satisfies individual rationality as well.
Towards a universal test suite for combinatorial auction algorithms
 In ACM Electronic Commerce
, 2000
"... General combinatorial auctions—auctions in which bidders place unrestricted bids for bundles of goods—are the subject of increasing study. Much of this work has focused on algorithms for finding an optimal or approximately optimal set of winning bids. Comparatively little attention has been paid to ..."
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Cited by 162 (11 self)
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General combinatorial auctions—auctions in which bidders place unrestricted bids for bundles of goods—are the subject of increasing study. Much of this work has focused on algorithms for finding an optimal or approximately optimal set of winning bids. Comparatively little attention has been paid to methodical evaluation and comparison of these algorithms. In particular, there has not been a systematic discussion of appropriate data sets that can serve as universally accepted and well motivated benchmarks. In this paper we present a suite of distribution families for generating realistic, economically motivated combinatorial bids in five broad realworld domains. We hope that this work will yield many comments, criticisms and extensions, bringing the community closer to a universal combinatorial auction test suite.
Tycoon: An Implementation of a Distributed, Marketbased Resource Allocation System”, Multiagent Grid Systems
"... Distributed clusters like the Grid and PlanetLab enable the same statistical multiplexing efficiency gains for computing as the Internet provides for networking. One major challenge is allocating resources in an economically efficient and lowlatency way. A common solution is proportional share, whe ..."
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Cited by 116 (8 self)
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Distributed clusters like the Grid and PlanetLab enable the same statistical multiplexing efficiency gains for computing as the Internet provides for networking. One major challenge is allocating resources in an economically efficient and lowlatency way. A common solution is proportional share, where users each get resources in proportion to their predefined weight. However, this does not allow users to differentiate the value of their jobs. This leads to economic inefficiency. In contrast, systems that require reservations impose a high latency (typically minutes to hours) to acquire resources. We present Tycoon, a market based distributed resource allocation system based on proportional share. The key advantages of Tycoon are that it allows users to differentiate the value of their jobs, its resource acquisition latency is limited only by communication delays, and it imposes no manual bidding overhead on users. We present experimental results using a prototype implementation of our design. 1
Solving Combinatorial Auctions using Stochastic Local Search
, 2000
"... Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determination for CAs is NPhard and recent algorithms have difficulty with problems involving goods and bids beyond the hundre ..."
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Cited by 106 (2 self)
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Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determination for CAs is NPhard and recent algorithms have difficulty with problems involving goods and bids beyond the hundreds. We apply a new stochastic local search algorithm, Casanova, to this problem, and demonstrate that it finds high quality (even optimal) solutions much faster than recently proposed methods (up to several orders of magnitude), particularly for large problems. We also propose a logical language for naturally expressing combinatorial bids in which a single logical bid corresponds to a large (often exponential) number of explicit bids. We show that Casanova performs much better than systematic methods on such problems.
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 99 (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.
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
A Market Protocol for Decentralized Task Allocation
 In The Proceedings of the Third International Conference on MultiAgent Systems (ICMAS98
, 1998
"... We present a decentralized market protocol for allocating tasks among agents that contend for scarce resources. Agents trade tasks and resources at prices determined by an auction protocol. We specify a simple set of bidding policies that, along with the auction mechanism, exhibits desirable converg ..."
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Cited by 89 (7 self)
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We present a decentralized market protocol for allocating tasks among agents that contend for scarce resources. Agents trade tasks and resources at prices determined by an auction protocol. We specify a simple set of bidding policies that, along with the auction mechanism, exhibits desirable convergence properties. The system always reaches quiescence. If the system reaches quiescence below the consumer 's reserve price for the high level task, it will be in a solution state. If the system finds a solution it will reach quiescence in a solution state. Experimental evidence supports our conjecture that the system will converge to a solution when one exists and the consumer bids sufficiently high. We describe the system's application to and implementation in an agentbased digital library. 1. Introduction In a multiagent system (MAS), we must often address the problem of allocating resources and effort in such a way that the resulting collection of agents can accomplish a complex task. T...