Fluctuation in Human Subjects Iterated Prisoner’s Dilemma Games

Abstract:     
How to examine a behavior model in social computation is a long existed problem. By data mining, characters of the fluctuation in human subjects iterated prisoner’s dilemma (IPD) experiment are studied. Fluctuation is the individual strategy changing. In IPD, fluctuation of a population is the average of the absolute value of strategy changing of individual over the whole population of an experimental session, and fluctuation of a group is over a group, and so on. Therefore, it’s natural to assume that there is a certain relationship between magnitude of fluctuation and deviation from equilibrium, namely, the more deviation from equilibrium, the more fluctuation. Here, the relationship is studied quantitatively. Employing row data from two recently articles (Duffy and Ochs [Game and Economics Behavior (2009)] and Yang, et al [Experimental Economics (2007)], we examined the above-mentioned relationship, the characters of the fluctuation near the fixed point limit and whole strategy range. In this note, the function of fluctuation is shown in three cases. (1) either at the session’s level, or at the subgame’s level, the average magnitude of fluctuation is positively and precisely related to the deviation from equilibrium; (2) the fluctuation can be quantitatively captured by random impulse model when a society is very close to pure Nash equilibrium point; (3) fluctuation can be used as a criterion for evaluating theoretical models. To sum up, the advantage of the fluctuation measurement is shown. This finding might be a useful judgment for the behavior modeling for social computations.

Number of Pages in PDF File: 9

Keywords: human subject experiment, fluctuation, metric, iterated prisoner dilemma, mixed equilibrium, noise

JEL Classification: C91, C92

working papers series