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  4. Fast convergence in evolutionary models: A Lyapunov approach

Fast convergence in evolutionary models: A Lyapunov approach

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Author(s)
Fudenberg, Drew
•
Imhof, Lorens A.
•
Ellison, Glenn David
Date Issued
November 2015
Journal
Journal of Economic Theory
Citation
Ellison, Glenn, Drew Fudenberg, and Lorens A. Imhof. “Fast Convergence in Evolutionary Models: A Lyapunov Approach.” Journal of Economic Theory 161 (January 2016): 1–36.
Version
Author's final manuscript
Abstract
Evolutionary models in which N players are repeatedly matched to play a game have “fast convergence” to a set A if the models both reach A quickly and leave A slowly, where “quickly” and “slowly” refer to whether the expected hitting and exit times remain bounded when N tends to infinity. We provide simple and general Lyapunov criteria which are sufficient for reaching quickly and leaving slowly. We use these criteria to determine aspects of learning models that promote fast convergence.
MIT Department
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/119847
DOI of Published Version
https://doi.org/10.1016/j.jet.2015.10.008
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