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| Dublin Core |
PKP Metadata Items |
Metadata for this document |
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| 1. |
Title |
Title of document |
Best experienced payoff dynamics and cooperation in the Centipede game |
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| 2. |
Creator |
Author's name, affiliation |
William H. Sandholm; Department of Economics, University of Wisconsin |
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| 2. |
Creator |
Author's name, affiliation |
Segismundo S. Izquierdo; Department of Industrial Organization and BioEcoUva, Universidad de Valladolid |
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| 2. |
Creator |
Author's name, affiliation |
Luis R. Izquierdo; Department of Management Engineering, Universidad de Burgos |
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| 3. |
Subject |
Subject(s) |
Evolutionary game theory, backward induction, Centipede game, computational algebra |
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| 3. |
Subject |
Subject classification |
C72, C73 |
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| 4. |
Description |
Abstract |
We study population game dynamics under which each revising agent tests each of his strategies a fixed number of times, with each play of each strategy being against a newly drawn opponent, and chooses the strategy whose total payoff was highest. In the Centipede game, these best experienced payoff dynamics lead to cooperative play. When strategies are tested once, play at the almost globally stable state is concentrated on the last few nodes of the game, with the proportions of agents playing each strategy being largely independent of the length of the game. Testing strategies many times leads to cyclical play. |
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| 5. |
Publisher |
Organizing agency, location |
Econometric Society |
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| 6. |
Contributor |
Sponsor(s) |
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| 7. |
Date |
(YYYY-MM-DD) |
2019-12-02 |
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| 8. |
Type |
Status & genre |
Peer-reviewed Article |
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| 8. |
Type |
Type |
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| 9. |
Format |
File format |
pdf
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| 10. |
Identifier |
Universal Resource Indicator |
https://econtheory.org/ojs/index.php/te/article/view/20191347 |
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| 11. |
Source |
Journal/conference title; vol., no. (year) |
Theoretical Economics; Volume 14, Number 4 (November 2019) |
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| 12. |
Language |
English=en |
en |
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| 15. |
Rights |
Copyright and permissions |
Authors who publish in Theoretical Economics will release their articles under the Creative Commons Attribution-NonCommercial license. This license allows anyone to copy and distribute the article for non-commercial purposes provided that appropriate attribution is given. |