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Asynchronous Learning in Decentralized Environments: A Game-Theoretic Approach

In: Collectives and the Design of Complex Systems

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  • Eric J. Friedman

    (Cornell University, School of Operations Research and Industrial Engineering)

Abstract

Many of the chapters in this book consider collectives that are cooperative; all agents work together to achieve a common goal—maximizing the “world utility function.” Often this is achieved by allowing agents to behave selfishly according to some “personal utility function,” although this utility function is explicitly imposed by the designer so is not truly “selfish.” In this chapter we consider the problems that arise when agents are truly selfish and their personal utility functions are intrinsic to their behavior. As designers we cannot directly alter these utility functions arbitrarily; all we can do is to adjust the ways in which the agents interact with each other and the system in order to achieve our own design goals. In game theory, this is the mechanism design problem, and the design goal is denoted the “social choice function” (SCF). 1

Suggested Citation

  • Eric J. Friedman, 2004. "Asynchronous Learning in Decentralized Environments: A Game-Theoretic Approach," Springer Books, in: Kagan Tumer & David Wolpert (ed.), Collectives and the Design of Complex Systems, chapter 4, pages 133-143, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4419-8909-3_4
    DOI: 10.1007/978-1-4419-8909-3_4
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