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Asynchronous Learning in Decentralized Environments: A Game-Theoretic Approach

  • Eric J. Friedman

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

Keywords

Utility Function Nash Equilibrium Congestion Control Solution Concept Forward Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Eric J. Friedman
    • 1
  1. 1.School of Operations Research and Industrial EngineeringCornell UniversityIthacaUSA

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