Predicting Human Cooperation

Nay JJ, Vorobeychik Y (May 2016) Predicting Human Cooperation. PLoS ONE 11(5)

19 Pages Posted: 21 Sep 2017

See all articles by John Nay

John Nay

New York University (NYU); Skopos Labs, Inc.

Yevgeniy Vorobeychik

Vanderbilt University, Department of Electrical Engineering and Computer Science

Date Written: February 9, 2016

Abstract

The Prisoner’s Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit. A strictly dominant strategy in a Prisoner’s Dilemma (defection), when played by both players, is mutually harmful. Repetition of the Prisoner’s Dilemma can give rise to cooperation as an equilibrium, but defection is as well, and this ambiguity is difficult to resolve. The numerous behavioral experiments investigating the Prisoner’s Dilemma highlight that players often cooperate, but the level of cooperation varies significantly with the specifics of the experimental predicament. We present the first computational model of human behavior in repeated Prisoner’s Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner. Our model relies on data we integrated from many experiments, comprising 168,386 individual decisions. The model is composed of two pieces: the first predicts the first-period action using solely the structural game parameters, while the second predicts dynamic actions using both game parameters and history of play. Our model is successful not merely at fitting the data, but in predicting behavior at multiple scales in experimental designs not used for calibration, using only information about the game structure. We demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation.

Keywords: machine learning

Suggested Citation

Nay, John and Nay, John and Vorobeychik, Yevgeniy, Predicting Human Cooperation (February 9, 2016). Nay JJ, Vorobeychik Y (May 2016) Predicting Human Cooperation. PLoS ONE 11(5), Available at SSRN: https://ssrn.com/abstract=3040600

John Nay (Contact Author)

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
20 Cooper Square 3rd Floor
New York, NY 10003-711
United States

Skopos Labs, Inc.

NY
United States

HOME PAGE: http://skoposlabs.com

Yevgeniy Vorobeychik

Vanderbilt University, Department of Electrical Engineering and Computer Science ( email )

2301 Vanderbilt Place
Nashville, TN 37240
United States

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