We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest. 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

We study auctions with severe bounds on the communication allowed: each bidder may only transmit t bits of information to the auctioneer. We consider both welfare-maximizing and revenuemaximizing auctions under this communication restriction. For both measures, we determine the optimal auction and show that the loss incurred relative to unconstrained auctions is mild. We prove non-surprising properties of these kinds of auctions, e.g. that discrete prices are informationally ecient, as well as some surprising properties, e.g. that asymmetric auctions are better than symmetric ones.

Abstract This paper considers algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest. 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 inter-connected 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.

Many recent applications of interest involve self-interested 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 self-interest. This led several researchers to consider computational models that are based on a sub-field of game-theory and micro-economics 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.

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