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62
On the power of randomization in algorithmic mechanism design
"... In many settings the power of truthful mechanisms is severely bounded. In this paper we use randomization to overcome this problem. In particular, we construct an FPTAS for multiunit auctions that is truthful in expectation, whereas there is evidence that no polynomialtime truthful deterministic m ..."
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Cited by 33 (9 self)
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In many settings the power of truthful mechanisms is severely bounded. In this paper we use randomization to overcome this problem. In particular, we construct an FPTAS for multiunit auctions that is truthful in expectation, whereas there is evidence that no polynomialtime truthful deterministic mechanism provides an approximation ratio better than 2. We also show for the first time that truthful in expectation polynomialtime mechanisms are provably stronger than polynomialtime universally truthful mechanisms. Specifically, we show that there is a setting in which: (1) there is a nonpolynomial time truthful mechanism that always outputs the optimal solution, and that (2) no universally truthful randomized mechanism can provide an approximation ratio better than 2 in polynomial time, but (3) an FPTAS that is truthful in expectation exists.
Externalities in online advertising
 In International World Wide Web Conference (WWW
, 2008
"... Most models for online advertising assume that an advertiser’s value from winning an ad auction, which depends on the clickthrough rate or conversion rate of the advertisement, is independent of other advertisements served alongside it in the same session. This ignores an important externality effec ..."
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Cited by 26 (2 self)
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Most models for online advertising assume that an advertiser’s value from winning an ad auction, which depends on the clickthrough rate or conversion rate of the advertisement, is independent of other advertisements served alongside it in the same session. This ignores an important externality effect: as the advertising audience has a limited attention span, a highquality ad on a page can detract attention from other ads on the same page. That is, the utility to a winner in such an auction also depends on the set of other winners. In this paper, we introduce the problem of modeling externalities in online advertising, and study the winner determination problem in these models. Our models are based on choice models on the audience side. We show that in the most general case, the winner determination problem is hard even to approximate. However, we give an approximation algorithm for this problem with an approximation factor that is logarithmic in the ratio of the maximum to the minimum bid. Furthermore, we show that there are some interesting special cases, such as the case where the audience preferences are single peaked, where the problem can be solved exactly in polynomial time. For all these algorithms, we prove that the winner determination algorithm can be combined with VCGstyle payments to yield truthful mechanisms.
Practical secrecypreserving, verifiably correct and trustworthy auctions
 In ICEC ’06: Proceedings of the 8th International Conference on Electronic Commerce
, 2006
"... We present a practical system for conducting sealedbid auctions that preserves the secrecy of the bids while providing for verifiable correctness and trustworthiness of the auction. The auctioneer must accept all bids submitted and follow the published rules of the auction. No party receives any us ..."
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Cited by 25 (7 self)
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We present a practical system for conducting sealedbid auctions that preserves the secrecy of the bids while providing for verifiable correctness and trustworthiness of the auction. The auctioneer must accept all bids submitted and follow the published rules of the auction. No party receives any useful information about bids before the auction closes and no bidder is able to change or repudiate her 1 bid. Our solution uses Paillier’s homomorphic encryption scheme [25] for zero knowledge proofs of correctness. Only minimal cryptographic technology is required of bidders; instead of employing complex interactive protocols or multiparty computation, the single auctioneer computes optimal auction results and publishes proofs of the results ’ correctness. Any party can check these proofs of correctness via publicly verifiable computations on encrypted bids. The system is illustrated through application to firstprice, uniformprice and secondprice auctions, including multiitem auctions. Our empirical results demonstrate the practicality of our method: auctions with hundreds of bidders are within reach of a single PC, while a modest distributed computing network can accommodate auctions with thousands of bids. 1.
Generalized Knapsack Solvers for MultiUnit Combinatorial Auctions: Analysis and Application to Computational Resource Allocation
 In Workshop on Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems
, 2004
"... The problem of allocating discrete computational resources motivates interest in general multiunit combinatorial exchanges. This paper considers the problem of computing optimal (surplusmaximizing) allocations, assuming unrestricted quasilinear preferences. We present a solver whose pseudopol ..."
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Cited by 23 (3 self)
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The problem of allocating discrete computational resources motivates interest in general multiunit combinatorial exchanges. This paper considers the problem of computing optimal (surplusmaximizing) allocations, assuming unrestricted quasilinear preferences. We present a solver whose pseudopolynomial time and memory requirements are linear in three of four natural measures of problem size: number of agents, length of bids, and units of each resource. In applications where the number of resource types is inherently a small constant, e.g., computational resource allocation, such a solver offers advantages over more elaborate approaches developed for highdimensional problems.
Marketbased task allocation mechanisms for limited capacity suppliers
 IEEE Trans on Systems, Man and Cybernetics (Part A
, 2007
"... Abstract — This paper reports on the design and comparison of two economicallyinspired mechanisms for task allocation in environments where sellers have finite production capacities and a cost structure composed of a fixed overhead cost and a constant marginal cost. Such mechanisms are required whe ..."
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Cited by 12 (4 self)
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Abstract — This paper reports on the design and comparison of two economicallyinspired mechanisms for task allocation in environments where sellers have finite production capacities and a cost structure composed of a fixed overhead cost and a constant marginal cost. Such mechanisms are required when a system consists of multiple selfinterested stakeholders that each possess private information that is relevant to solving a systemwide problem. Against this background, we first develop a computationally tractable centralised mechanism that finds the set of producers that have the lowest total cost in providing a certain demand (i.e. it is efficient). We achieve this by extending the standard VickreyClarkeGroves mechanism to allow for multiattribute bids and by introducing a novel penalty scheme such that producers are incentivised to truthfully report their capacities and their costs. Furthermore our extended mechanism is able to handle sellers ’ uncertainty about their production capacity and ensures that individual agents find it profitable to participate in the mechanism. However, since this first mechanism is centralised, we also develop a complementary decentralised mechanism based around the continuous double auction. Again because of the characteristics of our domain, we need to extend the standard form of this protocol by introducing a novel clearing rule based around an order book. With this modified protocol, we empirically demonstrate (with simple trading strategies) that the mechanism achieves high efficiency. In particular, despite this simplicity, the traders can still derive a profit from the market which makes our mechanism attractive since these results are a likely lower bound on their expected returns. Index Terms — distributed decision making, decision theory, multiagent systems, marketbased control. I.
Matching Models for Preferencesensitive Group Purchasing TYLER LU, University of Toronto
"... Matching buyers and sellers is one of the most fundamental problems in economics and market design. An interesting variant of the matching problem arises when selfinterested buyers come together in order to induce sellers to offer quantity or volume discounts, as is common in buying consortia, and ..."
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Cited by 9 (2 self)
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Matching buyers and sellers is one of the most fundamental problems in economics and market design. An interesting variant of the matching problem arises when selfinterested buyers come together in order to induce sellers to offer quantity or volume discounts, as is common in buying consortia, and more recently in the consumer group couponing space (e.g., Groupon). We consider a general model of this problem in which a group or buying consortium is faced with volume discount offers from multiple vendors, but group members have distinct preferences for different vendor offerings. Unlike some recent formulations of matching games that involve quantity discounts, the combination of varying preferences and discounts can render the core of the matching game empty, in both the transferable and nontransferable utility sense. Thus, instead of coalitional stability, we propose several forms of Nash stability under various epistemic and transfer/payment assumptions. We investigate the computation of buyerwelfare maximizing matchings and show the existence of transfers (subsidized prices) of a particularly desirable form that support stable matchings. We also study a nontransferable utility model, showing that stable matchings exist; and we develop a variant of the problem in which buyers provide a simple preference ordering over “deals ” rather than specific valuations—a model that is especially attractive in the consumer space—which also admits stable matchings. Computational experiments demonstrate the efficacy and value of our approach.
Quantifying the Strategyproofness of Mechanisms via
 Metrics on Payoff Distributions.” Proc. 17th National Conference on Artificial Intelligence (AAAI00
, 2009
"... Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budgetbalance, stability against deviations by coalitions, and computational tractability. In the search for ma ..."
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Cited by 9 (6 self)
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Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budgetbalance, stability against deviations by coalitions, and computational tractability. In the search for maximallystrategyproof mechanisms that simultaneously satisfy other desirable properties, we introduce a new metric to quantify the strategyproofness of a mechanism, based on comparing the payoff distribution, given truthful reports, against that of a strategyproof “reference” mechanism that solves a problem relaxation. Focusing on combinatorial exchanges, we demonstrate that the metric is informative about the eventual equilibrium, where simple regretbased metrics are not, and can be used for online selection of an effective mechanism. 1
Exact algorithms for procurement problems under a total quantity discount structure
 European Journal of Operational Research
, 2007
"... In this paper, we study the procurement problem faced by a buyer who needs to purchase a variety of goods from suppliers applying a socalled total quantity discount policy. This policy implies that every supplier announces a number of volume intervals and that the volume interval in which the total ..."
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Cited by 7 (3 self)
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In this paper, we study the procurement problem faced by a buyer who needs to purchase a variety of goods from suppliers applying a socalled total quantity discount policy. This policy implies that every supplier announces a number of volume intervals and that the volume interval in which the total amount ordered lies determines the discount. Moreover, the discounted prices apply to all goods bought from the supplier, not only to those goods exceeding the volume threshold. We refer to this costminimization problem as the TQD problem. We give a mathematical formulation for this problem and argue that not only it is NPhard, but also that there exists no polynomialtime approximation algorithm with a constant ratio (unless P = NP). Apart from the basic form of the TQD problem, we describe three variants. In a first variant, the market share that one or more suppliers can obtain is constrained. Another variant allows the buyer to procure more goods than strictly needed, in order to reach a lower total cost. In a third variant, the number of winning suppliers is limited. We show that the TQD problem and its variants can be solved by solving a series of mincost flow problems. Finally, we investigate the performance of three exact algorithms (mincost flow based branchandbound, linear programming based branchandbound, and branchandcut) on randomly generated instances involving 50 suppliers and 100 goods. It turns out that even the large instances of the basic problem are solved to optimality within a limited amount of time. However, we find that different algorithms perform best in terms of computation time for different variants.
HardtoManipulate VCGBased Auctions
, 2004
"... Mechanism design provides a framework to solve distributed optimization problems in systems of selfinterested agents. The combinatorial auction is one such problem, in which there is a set of discrete items to allocate to agents. Unfortunately, recent results suggest that it is impossible to imp ..."
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Cited by 6 (0 self)
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Mechanism design provides a framework to solve distributed optimization problems in systems of selfinterested agents. The combinatorial auction is one such problem, in which there is a set of discrete items to allocate to agents. Unfortunately, recent results suggest that it is impossible to implement reasonable approximations without losing robustness to manipulation. Furthermore, the VickreyClarkeGroves (VCG) mechanism is known to be vulnerable to manipulation when agents can bid under multiple false names. In this paper we relax incentive constraints and require only that useful manipulation be NPhard. We prove that any tractable approximation algorithm can be made to produce a hardtomanipulate (VCGbased) mechanism, providing a useful counterpoint to these negative results. We also show that falsename bid manipulation in the VCG is NPhard.
Five AI Challenges in Strategyproof Computing
, 2003
"... Computational systems are now distributed by default, and designed, owned and used by multiple selfinterested parties. In the face of this growing system complexity, we need a unifying design paradigm, that supports continued innovation and competition while promoting easy deployment, operati ..."
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Cited by 4 (3 self)
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Computational systems are now distributed by default, and designed, owned and used by multiple selfinterested parties. In the face of this growing system complexity, we need a unifying design paradigm, that supports continued innovation and competition while promoting easy deployment, operation, and use. Focusing on the central problem of resource allocationthe arbitration of shared resources among the competing demands of userswe introduce a paradigm of strategyproof computing, a vision in which individual users can treat other resources as their own. We layout the benefits of strategyproof computing, and identify five AI challenges in making this vision a reality.