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How Noise Matters

Author

Listed:
  • Lawrence E. Blume

    (Cornell University)

Abstract
Recent advances in evolutionary game theory have employed stochastic processes of noise in decisionmaking to select in favor of certain equilibria in coordination games. Noisy decisionmaking is justified on bounded rationality grounds, and consequently the sources of noise are left unmodelled. This methodological approach can only be successful if the results do not depend too much on the nature of the noise process. This paper investigates invariance to noise of the equilibrium selection results, both for the random matching paradigm that has characterized much of the recent literature and for a larger class of two-strategy population games where payoffs may vary non-linearly with the distribution of strategies among the population. Several parametrizations of noise reduction are investigated. The results show that a symmetry property of the noise process and (in the case of non-linear payoffs) bounds on the asymmetry of the payoff functions suffice to preserve the selection results of the evolutionary literature.

Suggested Citation

  • Lawrence E. Blume, 1994. "How Noise Matters," Game Theory and Information 9407002, University Library of Munich, Germany, revised 27 Jul 1994.
  • Handle: RePEc:wpa:wuwpga:9407002
    Note: One TeX file (24 pages) and an EPS file, queries to LB19@CORNELL.EDU
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    References listed on IDEAS

    as
    1. Brock, William A. & Durlauf, Steven N., 2001. "Interactions-based models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 54, pages 3297-3380, Elsevier.
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    More about this item

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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