Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217105 
Year of Publication: 
2019
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 14 [Issue:] 4 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2019 [Pages:] 1347-1385
Publisher: 
The Econometric Society, New Haven, CT
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.
Subjects: 
Evolutionary game theory
backward induction
Centipede game
computational algebra
JEL: 
C72
C73
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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