Stochastic Evolution with Slow Learning.

This paper studies the extent to which diusion approximations provide a reliable guide to equilibrium selection results in nite games. It is shown that they do for a class of nite games with weak learning provided that limits are taken in a certain order. The paper also shows that making mutation ra...

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Main Author: Beggs, A
Format: Working paper
Language:English
Published: Department of Economics (University of Oxford) 2000
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author Beggs, A
author_facet Beggs, A
author_sort Beggs, A
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description This paper studies the extent to which diusion approximations provide a reliable guide to equilibrium selection results in nite games. It is shown that they do for a class of nite games with weak learning provided that limits are taken in a certain order. The paper also shows that making mutation rates small does not in general select a unique equilibrium but making selection strong does.
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spelling oxford-uuid:aea2086d-5a87-442c-983c-5cd32a71c49c2022-03-27T03:43:52ZStochastic Evolution with Slow Learning.Working paperhttp://purl.org/coar/resource_type/c_8042uuid:aea2086d-5a87-442c-983c-5cd32a71c49cEnglishDepartment of Economics - ePrintsDepartment of Economics (University of Oxford)2000Beggs, AThis paper studies the extent to which diusion approximations provide a reliable guide to equilibrium selection results in nite games. It is shown that they do for a class of nite games with weak learning provided that limits are taken in a certain order. The paper also shows that making mutation rates small does not in general select a unique equilibrium but making selection strong does.
spellingShingle Beggs, A
Stochastic Evolution with Slow Learning.
title Stochastic Evolution with Slow Learning.
title_full Stochastic Evolution with Slow Learning.
title_fullStr Stochastic Evolution with Slow Learning.
title_full_unstemmed Stochastic Evolution with Slow Learning.
title_short Stochastic Evolution with Slow Learning.
title_sort stochastic evolution with slow learning
work_keys_str_mv AT beggsa stochasticevolutionwithslowlearning