Best experienced payoff dynamics and cooperation in the centipede game
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...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Burgos (UBU) |
| Repositorio: | Repositorio Institucional de la Universidad de Burgos (RIUBU) |
| OAI Identifier: | oai:riubu.ubu.es:10259/5236 |
| Acceso en línea: | http://hdl.handle.net/10259/5236 |
| Access Level: | acceso abierto |
| Palabra clave: | Evolutionary game theory backward induction centipede game computational algebra Economía Economics |
| Sumario: | 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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