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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 634 (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
Competitive auctions and digital goods
 IN PROC. 12TH SYMP. ON DISCRETE ALG
, 2001
"... We study a class of single round, sealed bid auctions for items in unlimited supply such as digital goods. We focus on auctions that are truthful and competitive. Truthful auctions encourage bidders to bid their utility; competitive auctions yield revenue within a constant factor of the revenue fo ..."
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Cited by 133 (27 self)
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We study a class of single round, sealed bid auctions for items in unlimited supply such as digital goods. We focus on auctions that are truthful and competitive. Truthful auctions encourage bidders to bid their utility; competitive auctions yield revenue within a constant factor of the revenue for optimal fixed pricing. We show that for any truthful auction, even a multiprice auction, the expected revenue does not exceed that for optimal fixed pricing. We also give a bound on how far the revenue for optimal fixed pricing can be from the total market utility. We show that several randomized auctions are truthful and competitive under certain assumptions, and that no truthful deterministic auction is competitive. We present simulation results which confirm that our auctions compare favorably to fixed pricing. Some of our results extend to bounded supply markets, for which we also get truthful and competitive auctions.
Algorithms for selfish agents: Mechanism design for distributed computation
 In Proceedings of the 16th Annual Symposium on Theoretical Aspects of Computer Science
, 1999
"... Abstract This paper considers algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. Such scenarios arise, in particular, when computers or users aim to cooperate or trade over the Internet. As such participa ..."
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Cited by 36 (1 self)
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Abstract This paper considers algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. Such scenarios arise, in particular, when computers or users aim to cooperate or trade over the Internet. 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. This exposition presents a model to formally study such algorithms. This model, based on the field of mechanism design, is taken from the author's joint work with Amir Ronen, and is similar to approaches taken in the distributed AI community in recent years. Using this model, we demonstrate how some of the techniques of mechanism design can be applied towards distributed computation problems. We then exhibit some issues that arise in distributed computation which require going beyond the existing theory of mechanism design. 1 Introduction A large part of research in computer science is concerned with protocols and algorithms for interconnected collections of computers. The designer of such an algorithm or protocol always makes an implicit assumption that the participating computers will act as instructed except, perhaps, for the faulty or malicious ones.