Evolutionary Cycles of Cooperation and Defection

DSpace/Manakin Repository

Evolutionary Cycles of Cooperation and Defection

Citable link to this page


Title: Evolutionary Cycles of Cooperation and Defection
Author: Imhof, Lorens A.; Fudenberg, Drew; Nowak, Martin A.

Note: Order does not necessarily reflect citation order of authors.

Citation: Imhof, Lorens A., Drew Fudenberg, Martin A. Nowak. 2005. Evolutionary cycles of cooperation and defection. Proceedings of the National Academy of Sciences USA 102(31): 10797-10800.
Full Text & Related Files:
Abstract: The main obstacle for the evolution of cooperation is that natural selection favors defection in most settings. In the repeated prisoner's dilemma, two individuals interact several times, and, in each round, they have a choice between cooperation and defection. We analyze the evolutionary dynamics of three simple strategies for the repeated prisoner's dilemma: always defect (ALLD), always cooperate (ALLC), and tit-for-tat (TFT). We study mutation–selection dynamics in finite populations. Despite ALLD being the only strict Nash equilibrium, we observe evolutionary oscillations among all three strategies. The population cycles from ALLD to TFT to ALLC and back to ALLD. Most surprisingly, the time average of these oscillations can be entirely concentrated on TFT. In contrast to the classical expectation, which is informed by deterministic evolutionary game theory of infinitely large populations, stochastic evolution of finite populations need not choose the strict Nash equilibrium and can therefore favor cooperation over defection.
Published Version: doi:10.1073/pnas.0502589102
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4554745
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)


Search DASH

Advanced Search