Departmental Papers (ASC)
Title
Resilient Cooperators Stabilize Long-run Cooperation In The Finitely Repeated Prisoner’s Dilemma
Document Type
Journal Article
Date of this Version
1-13-2017
Publication Source
Nature Communications
Start Page
1
Last Page
10
DOI
10.1038/ncomms13800
Abstract
Learning in finitely repeated games of cooperation remains poorly understood in part because their dynamics play out over a timescale exceeding that of traditional lab experiments. Here, we report results of a virtual lab experiment in which 94 subjects play up to 400 ten-round games of Prisoner’s Dilemma over the course of twenty consecutive weekdays. Consistent with previous work, the typical round of first defection moves earlier for several days; however, this unravelling process stabilizes after roughly one week. Analysing individual strategies, we find that approximately 40% of players behave as resilient cooperators who avoid unravelling even at significant cost to themselves. Finally, using a standard learning model we predict that a sufficiently large minority of resilient cooperators can permanently stabilize unravelling among a majority of rational players. These results shed hopeful light on the long-term dynamics of cooperation, and demonstrate the importance of long-run experiments.
Copyright/Permission Statement
Copyright © 2017, The Author(s) This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Recommended Citation
Mao, A., Dworkin, L., Suri, S., & Watts, D. J. (2017). Resilient Cooperators Stabilize Long-run Cooperation In The Finitely Repeated Prisoner’s Dilemma. Nature Communications, 1-10. https://doi.org/10.1038/ncomms13800
Date Posted: 20 March 2023
This document has been peer reviewed.
Comments
Note: At the time of this publication, Dr. Duncan Watts was affiliated with Microsoft Research. Currently, Dr. Duncan J. Watts is Stevens University Professor at the University of Pennsylvania, and Professor in Department of Computer and Information Science in the School of Engineering and Applied Science, Annenberg School for Communication, and Department of Operations, Information and Decisions in the Wharton School.