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
computational 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 extremely 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.Comment: Added references. New inline citation style. Added small portions of
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