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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 678 (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
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 222 (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.
An introduction to collective intelligence
 Handbook of Agent technology. AAAI
, 1999
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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 107 (6 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.
A survey of collectives
 IN COLLECTIVES AND THE DESIGN OF COMPLEX SYSTEMS
, 2004
"... Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a welldefined set of systemlevel performance cr ..."
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Cited by 29 (12 self)
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Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a welldefined set of systemlevel performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of a large number of agents leads to “coordinated ” behavior on the global scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple rovers, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is expected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.
Vickrey Pricing in Network Routing: Fast Payment Computation
 In Proc. of the 42nd IEEE Symposium on Foundations of Computer Science
, 2001
"... Eliciting truthful responses from selfinterested agents is an important problem in game theory and microeconomics, and it is studied under mechanism design or implementation theory. Truthful mechanisms have received considerable interest within computer science recently for designing protocols f ..."
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Cited by 24 (0 self)
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Eliciting truthful responses from selfinterested agents is an important problem in game theory and microeconomics, and it is studied under mechanism design or implementation theory. Truthful mechanisms have received considerable interest within computer science recently for designing protocols for Internetbased applications, which typically involve cooperation of multiple selfinterested agents. A cornerstone of the mechanism design field is the Vickrey mechanism, or more generally the class of VickreyClarkeGroves mechanisms. These mechanisms are known to be incentivecompatible, meaning that rational agents maximize their utility by truthfully revealing their preferences. In the VickreyClarkeGroves (VCG) mechanism, each agent receives a "payment" for his participation, and this payment is proportional to the added "value" he brings to the system. Implementing the VCG mechanism often requires solving a (nontrivial) optimization problem n + 1 times, once with all agents, and once corresponding to each agent's deletion to determine his incremental value. An important algorithmic challenge is to reduce this computational overhead.
Algorithms for Rational Agents
 In Proc. of the 27th Annual Conference on Current Trends in Theory and Practice of Informatics
, 2000
"... Many recent applications of interest involve selfinterested participants. As such participants, termed agents, may manipulate the algorithm for their own benefit, a new challenge emerges: The design of algorithms and protocols that perform well when the agents behave according to their own selfint ..."
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Cited by 17 (3 self)
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Many recent applications of interest involve selfinterested participants. As such participants, termed agents, may manipulate the algorithm for their own benefit, a new challenge emerges: The design of algorithms and protocols that perform well when the agents behave according to their own selfinterest. This led several researchers to consider computational models that are based on a subfield of gametheory and microeconomics called mechanism design. This paper introduces this topic mainly through examples. It demonstrates that in many cases selfishness can be satisfactorily overcome, surveys some of the recent trends in this area and presents new challenging problems. The paper is mostly based on classic results from mechanism design as well as on recent work by the author and others.