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

The field of economic mechanism design has been an active area of research in economics for at least 20 years. This field uses the tools of economics and game theory to design "rules of interaction " for economic transactions that will, in principle, yield some desired outcome. In this paper I provide an overview of this subject for an audience interested in applications to electronic commerce and discuss some special problems that arise in this context.

This thesis presents flexible abstractions for specifying resource management policies, together with efficient mechanisms for implementing those abstractions. Several novel scheduling techniques are introduced, including both randomized and deterministic algorithms that provide proportional-share control over resource consumption rates. Such control is beyond the capabilities of conventional schedulers, and is desirable across a broad spectrum of systems that service clients of varying importance. Proportional-share scheduling is examined for several diverse resources, including processor time, memory, access to locks, and disk bandwidth. Resource rights are encapsulated by abstract, first-class objects called tickets. An active client consumes resources at a rate proportional to the number of tickets that it holds. Tickets can be issued in different amounts and may be transferred between clients. A modular currency abstraction is also introduced to flexibly name, share, and protect ...

In this paper, we propose an architecture for an agent-based virtual market that includes all elements required for simulating a real market. These elements include a communication infrastructure, mechanisms for storage and transfer of goods, banking and monetary transactions, and economic mechanisms for direct or brokered producerconsumer transactions. We report findings that resulted from implementing and conducting experiments with a free-market agent architecture (MAGMA). MAGMA is an extensible architecture that provides all services essential to agent-based commercial activities. These services are available through an open-standard messaging API, which allows using a heterogeneous set of agents, independently of the platform and language. 1 Introduction Development of the Internet has spurred a number of attempts to create a virtual marketplace, where agents, both human-controlled and equipped with intelligent algorithms, can participate in trading of physical and electronic goo...

Visionary projections of a wide-area network teeming with intelligent agents describe an environment where end-users and their agents can pick and choose among a great variety of potentially valuable information services. However, neither network capabilities nor users' time and money are infinite. Computational markets provide one type of mechanism for allocating limited resources in such an environment in a distributed, dynamic way. Moreover, the underlying economic theory provides an analytical framework for predicting aggregate behavior and designing individual agents. In this paper, we describe a prototypical computational market model for information services distributed over a network. Our initial focus is on the economic problem of when and where to establish mirror sites for the more popular information services. Competitive agents choose to set up mirrors based on going prices for network bandwidth, computational resources, and the information service. Depending on the experi...

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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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This paper presents and evaluates a decision making framework that enables autonomous agents to dynamically select the mechanism they employ in order to coordinate their inter-related activities. Adopting this framework means coordination mechanisms move from the realm of something that is imposed upon the system at design time, to something that the agents select at run-time in order to fit their prevailing circumstances and their current coordination needs. Using this framework, agents make informed choices about when and how to coordinate and when to respond to requests for coordination. The framework is empirically evaluated, in a grid world scenario, and we highlight those types of environments in which it is e#ective.

One of the predominant modes of accessing information in the World Wide Web consists in surfing from one document to another along hypermedia links. We have studied the dynamics of Web surfing within an economics context by considering that there is value in each page that an individual visits, and that clicking on the next page assumes that the information will continue to have some value. Within this formulation an individual will continue to surf until the expected cost of continuing is perceived to be larger than the expected value of the information to be found in the future. This problem is similar to that of a real option in financial economics. We consider the options viewpoint as a descriptive theory of information foraging by Internet users, and we show how it leads to a kind of “law of surfing ” which has been verified experimentally in several large independent datasets. But the real options perspective, which is by now a well-established field in financial economics, may also provide a rich normative model for designing rational Internet agents.