Learning to Forgive.

The Folk Theorem for infinitely repeated games o®ers an embarrassment of riches; nowhere is equilibrium multiplicity more acute. This paper selects amongst these equilibria in the following sense. If players learn to play an infinitely repeated game using classical hypothesis testing, it is known th...

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Main Author: Norman, T
Format: Working paper
Language:English
Published: Department of Economics (University of Oxford) 2006
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author Norman, T
author_facet Norman, T
author_sort Norman, T
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description The Folk Theorem for infinitely repeated games o®ers an embarrassment of riches; nowhere is equilibrium multiplicity more acute. This paper selects amongst these equilibria in the following sense. If players learn to play an infinitely repeated game using classical hypothesis testing, it is known that their strategies almost always approximate equilibria of the repeated game. It is shown here that if, in addition, they are sufficiently "conservative" in adopting their hypotheses, then almost all of the time is spent approximating an efficient subset of equilibria that share a "forgiving" property. This result provides theoretical justification for the general sense amongst practitioners that efficiency is focal in such games.
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spelling oxford-uuid:06fd53ec-4d62-439b-874b-c86719275b6f2022-03-26T09:05:16ZLearning to Forgive.Working paperhttp://purl.org/coar/resource_type/c_8042uuid:06fd53ec-4d62-439b-874b-c86719275b6fEnglishOxford University Research Archive - ValetDepartment of Economics (University of Oxford)2006Norman, TThe Folk Theorem for infinitely repeated games o®ers an embarrassment of riches; nowhere is equilibrium multiplicity more acute. This paper selects amongst these equilibria in the following sense. If players learn to play an infinitely repeated game using classical hypothesis testing, it is known that their strategies almost always approximate equilibria of the repeated game. It is shown here that if, in addition, they are sufficiently "conservative" in adopting their hypotheses, then almost all of the time is spent approximating an efficient subset of equilibria that share a "forgiving" property. This result provides theoretical justification for the general sense amongst practitioners that efficiency is focal in such games.
spellingShingle Norman, T
Learning to Forgive.
title Learning to Forgive.
title_full Learning to Forgive.
title_fullStr Learning to Forgive.
title_full_unstemmed Learning to Forgive.
title_short Learning to Forgive.
title_sort learning to forgive
work_keys_str_mv AT normant learningtoforgive