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2,544
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 674 (21 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
Sprite: A Simple, CheatProof, CreditBased System for Mobile AdHoc Networks
 in Proceedings of IEEE INFOCOM
, 2002
"... Mobile ad hoc networking has been an active research area for several years. How to stimulate cooperation among selfish mobile nodes, however, is not well addressed yet. In this paper, we propose Sprite, a simple, cheatproof, creditbased system for stimulating cooperation among selfish nodes in mob ..."
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Cited by 473 (18 self)
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Mobile ad hoc networking has been an active research area for several years. How to stimulate cooperation among selfish mobile nodes, however, is not well addressed yet. In this paper, we propose Sprite, a simple, cheatproof, creditbased system for stimulating cooperation among selfish nodes in mobile ad hoc networks. Our system provides incentive for mobile nodes to cooperate and report actions honestly. Compared with previous approaches, our system does not require any tamperproof hardware at any node. Furthermore, we present a formal model of our system and prove its properties. Evaluations of a prototype implementation show that the overhead of our system is small. Simulations and analysis show that mobile nodes can cooperate and forward each other's messages, unless the resource of each node is extremely low.
Complex networks: Structure and dynamics
, 2006
"... Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is t ..."
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Cited by 428 (9 self)
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Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to model them as graphs whose nodes represent the dynamical units, and whose links stand for the interactions between them. On the one hand, scientists have to cope with structural issues, such as characterizing the topology of a complex wiring architecture, revealing the unifying principles that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. On the other hand, many relevant questions arise when studying complex networks ’ dynamics, such as learning how a large ensemble of dynamical systems that interact through a complex wiring topology can behave collectively. We review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines,
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
, 1998
"... In this paper, we adopt generalsum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zerosum stochastic games to a broader framework. We design a multiagent Qlearning method under this framework, and prove that it converges to a Na ..."
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Cited by 330 (4 self)
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In this paper, we adopt generalsum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zerosum stochastic games to a broader framework. We design a multiagent Qlearning method under this framework, and prove that it converges to a Nash equilibrium under specified conditions. This algorithm is useful for finding the optimal strategy when there exists a unique Nash equilibrium in the game. When there exist multiple Nash equilibria in the game, this algorithm should be combined with other learning techniques to find optimal strategies.
The complexity of computing a Nash equilibrium
, 2006
"... We resolve the question of the complexity of Nash equilibrium by showing that the problem of computing a Nash equilibrium in a game with 4 or more players is complete for the complexity class PPAD. Our proof uses ideas from the recentlyestablished equivalence between polynomialtime solvability of n ..."
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Cited by 324 (23 self)
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We resolve the question of the complexity of Nash equilibrium by showing that the problem of computing a Nash equilibrium in a game with 4 or more players is complete for the complexity class PPAD. Our proof uses ideas from the recentlyestablished equivalence between polynomialtime solvability of normalform games and graphical games, and shows that these kinds of games can implement arbitrary members of a PPADcomplete class of Brouwer functions. 1
Sharing the Cost of Multicast Transmissions
, 2001
"... We investigate costsharing algorithms for multicast transmission. Economic considerations point to two distinct mechanisms, marginal cost and Shapley value, as the two solutions most appropriate in this context. We prove that the former has a natural algorithm that uses only two messages per link o ..."
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Cited by 291 (19 self)
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We investigate costsharing algorithms for multicast transmission. Economic considerations point to two distinct mechanisms, marginal cost and Shapley value, as the two solutions most appropriate in this context. We prove that the former has a natural algorithm that uses only two messages per link of the multicast tree, while we give evidence that the latter requires a quadratic total number of messages. We also show that the welfare value achieved by an optimal multicast tree is NPhard to approximate within any constant factor, even for boundeddegree networks. The lowerbound proof for the Shapley value uses a novel algebraic technique for bounding from below the number of messages exchanged in a distributed computation; this technique may prove useful in other contexts as well.
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 ..."
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Cited by 277 (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. 1
Selfish Routing and the Price of Anarchy
 MATHEMATICAL PROGRAMMING SOCIETY NEWSLETTER
, 2007
"... Selfish routing is a classical mathematical model of how selfinterested users might route traffic through a congested network. The outcome of selfish routing is generally inefficient, in that it fails to optimize natural objective functions. The price of anarchy is a quantitative measure of this in ..."
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Cited by 252 (11 self)
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Selfish routing is a classical mathematical model of how selfinterested users might route traffic through a congested network. The outcome of selfish routing is generally inefficient, in that it fails to optimize natural objective functions. The price of anarchy is a quantitative measure of this inefficiency. We survey recent work that analyzes the price of anarchy of selfish routing. We also describe related results on bounding the worstpossible severity of a phenomenon called Braess’s Paradox, and on three techniques for reducing the price of anarchy of selfish routing. This survey concentrates on the contributions of the author’s PhD thesis, but also discusses several more recent results in the area.
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 250 (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.
Incentives For Sharing in PeertoPeer Networks
, 2001
"... Abstract. We consider the freerider problem in peertopeer file sharing networks such as Napster: that individual users are provided with no incentive for adding value to the network. We examine the design implications of the assumption that users will selfishly act to maximize their own rewards, ..."
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Cited by 244 (0 self)
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Abstract. We consider the freerider problem in peertopeer file sharing networks such as Napster: that individual users are provided with no incentive for adding value to the network. We examine the design implications of the assumption that users will selfishly act to maximize their own rewards, by constructing a formal game theoretic model of the system and analyzing equilibria of user strategies under several novel payment mechanisms. We support and extend this workwith results from experiments with a multiagent reinforcement learning model. 1