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14
Sharing the Cost of Multicast Transmissions
 Journal of Computer and System Sciences
, 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 249 (18 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. 1
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 224 (14 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
Algorithms, Games, and the Internet
 In STOC
, 2001
"... If the Internet is the next great subject for Theoretical Computer Science to model and illuminate mathematically, then Game Theory, and Mathematical Economics more generally, are likely to prove useful tools. In this talk I survey some opportunities and challenges in this important frontier. 1. ..."
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Cited by 135 (0 self)
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If the Internet is the next great subject for Theoretical Computer Science to model and illuminate mathematically, then Game Theory, and Mathematical Economics more generally, are likely to prove useful tools. In this talk I survey some opportunities and challenges in this important frontier. 1.
Overcoming Freeriding Behavior in PeertoPeer Systems
 ACM Sigecom Exchanges
, 2005
"... While the fundamental premise of peertopeer (P2P) systems is that of voluntary resource sharing among individual peers, there is an inherent tension between individual rationality and collective welfare that threatens the viability of these systems. This paper surveys recent research at the inters ..."
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Cited by 48 (0 self)
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While the fundamental premise of peertopeer (P2P) systems is that of voluntary resource sharing among individual peers, there is an inherent tension between individual rationality and collective welfare that threatens the viability of these systems. This paper surveys recent research at the intersection of economics and computer science that targets the design of distributed systems consisting of rational participants with diverse and selfish interests. In particular, we discuss major findings and open questions related to freeriding in P2P systems: factors affecting the degree of freeriding, incentive mechanisms to encourage user cooperation, and challenges in the design of incentive mechanisms for P2P systems.
HiddenAction in MultiHop Routing
, 2004
"... In any multihop routing scheme, cooperation by the intermediate nodes are essential for the succesful delivery of traffic. However, the effort exerted by the intermediate nodes are often unobservable by the source and/or destination nodes. We show it is possible to overcome this problem of hidden a ..."
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Cited by 24 (5 self)
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In any multihop routing scheme, cooperation by the intermediate nodes are essential for the succesful delivery of traffic. However, the effort exerted by the intermediate nodes are often unobservable by the source and/or destination nodes. We show it is possible to overcome this problem of hidden action by designing contracts, in the form of payments, to induce cooperation from the intermediate nodes. Interestingly, the ability to monitor perhop or perpath outcomes, even if costless to implement, may not improve the welfare of the participants or the performance of the network.
Using Genetic Programming to Optimise Pricing Rules for a Double Auction Market
, 2000
"... The mechanism design problem in economics is about designing rules of interaction for market games so they yield a globally desirable result in the face of selfinterested agents. This problem, which is of importance for ecommerce since much ecommerce is carried out through auctions, can be extremel ..."
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Cited by 16 (12 self)
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The mechanism design problem in economics is about designing rules of interaction for market games so they yield a globally desirable result in the face of selfinterested agents. This problem, which is of importance for ecommerce since much ecommerce is carried out through auctions, can be extremely complex. Traditionally, economists have tried using game theory and other formal methods to construct suitable mechanism rules. However, analytical methods typically oversimplify the problem and so the resulting rules are not necessarily robust. In this paper, we report on an alternative approach which we hope will eventually yield more robust solutions. Our methodology views mechanism design as a multiobjective optimisation problem and addresses the problem using genetic programming.
Multiagent Learning in Large Anonymous Games
"... In large systems, it is important for agents to learn to act effectively, but sophisticated multiagent learning algorithms generally do not scale. An alternative approach is to find restricted classes of games where simple, efficient algorithms converge. It is shown that stage learning efficiently ..."
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Cited by 2 (0 self)
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In large systems, it is important for agents to learn to act effectively, but sophisticated multiagent learning algorithms generally do not scale. An alternative approach is to find restricted classes of games where simple, efficient algorithms converge. It is shown that stage learning efficiently converges to Nash equilibria in large anonymous games if bestreply dynamics converge. Two features are identified that improve convergence. First, rather than making learning more difficult, more agents are actually beneficial in many settings. Second, providing agents with statistical information about the behavior of others can significantly reduce the number of observations needed.