Fast convergence in evolutionary models: A Lyapunov approach
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...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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2019
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| Online Access: | http://hdl.handle.net/1721.1/119847 https://orcid.org/0000-0003-3164-0855 |
| _version_ | 1826214120367587328 |
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| author | Fudenberg, Drew Imhof, Lorens A. Ellison, Glenn David |
| author2 | Massachusetts Institute of Technology. Department of Economics |
| author_facet | Massachusetts Institute of Technology. Department of Economics Fudenberg, Drew Imhof, Lorens A. Ellison, Glenn David |
| author_sort | Fudenberg, Drew |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T15:59:50Z |
| format | Article |
| id | mit-1721.1/119847 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:59:50Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | mit-1721.1/1198472022-09-29T17:36:56Z Fast convergence in evolutionary models: A Lyapunov approach Fudenberg, Drew Imhof, Lorens A. Ellison, Glenn David Massachusetts Institute of Technology. Department of Economics Ellison, Glenn David 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. 2019-01-04T14:49:20Z 2019-01-04T14:49:20Z 2015-11 2015-08 Article http://purl.org/eprint/type/JournalArticle 0022-0531 http://hdl.handle.net/1721.1/119847 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. https://orcid.org/0000-0003-3164-0855 en_US http://dx.doi.org/10.1016/j.jet.2015.10.008 Journal of Economic Theory Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Other univ. web domain |
| spellingShingle | Fudenberg, Drew Imhof, Lorens A. Ellison, Glenn David Fast convergence in evolutionary models: A Lyapunov approach |
| title | Fast convergence in evolutionary models: A Lyapunov approach |
| title_full | Fast convergence in evolutionary models: A Lyapunov approach |
| title_fullStr | Fast convergence in evolutionary models: A Lyapunov approach |
| title_full_unstemmed | Fast convergence in evolutionary models: A Lyapunov approach |
| title_short | Fast convergence in evolutionary models: A Lyapunov approach |
| title_sort | fast convergence in evolutionary models a lyapunov approach |
| url | http://hdl.handle.net/1721.1/119847 https://orcid.org/0000-0003-3164-0855 |
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