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Title: Predicting Human Cooperation

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.more » As a result, we demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation.« less

Authors:
 [1];  [1];  [2]
  1. Vanderbilt Univ., Nashville, TN (United States)
  2. Tianjin Univ. of Technology (China)
Publication Date:
Research Org.:
Vanderbilt Univ., Nashville, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1377075
Resource Type:
Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 11; Journal Issue: 5; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 60 APPLIED LIFE SCIENCES; Game theory; Prisoner's dilemma; Games; Behavior; Inertia; Forecasting; Simulation and modeling; Experimental design

Citation Formats

Nay, John J., Vorobeychik, Yevgeniy, and Xia, Cheng -Yi. Predicting Human Cooperation. United States: N. p., 2016. Web. doi:10.1371/journal.pone.0155656.
Nay, John J., Vorobeychik, Yevgeniy, & Xia, Cheng -Yi. Predicting Human Cooperation. United States. doi:10.1371/journal.pone.0155656.
Nay, John J., Vorobeychik, Yevgeniy, and Xia, Cheng -Yi. Thu . "Predicting Human Cooperation". United States. doi:10.1371/journal.pone.0155656. https://www.osti.gov/servlets/purl/1377075.
@article{osti_1377075,
title = {Predicting Human Cooperation},
author = {Nay, John J. and Vorobeychik, Yevgeniy and Xia, Cheng -Yi},
abstractNote = {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. As a result, we demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation.},
doi = {10.1371/journal.pone.0155656},
journal = {PLoS ONE},
number = 5,
volume = 11,
place = {United States},
year = {2016},
month = {5}
}

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