Abstract
Abstract
Behavioral experiments on the Ultimatum game have shown that we human beings have a remarkable preference in fair play, contradicting the predictions by the game theory. Most of the existing models seeking for explanations, however, strictly follow the assumption of Homo economicus in orthodox economics that people are self-interested and fully rational to maximize their earnings. Here we relax this assumption by allowing that people probabilistically choose to be ‘good Samaritans’, acting as fair players from time to time. For well-mixed and homogeneously structured populations, we numerically show that as this probability increases the level of fairness undergoes from the low scenario abruptly to the full fairness state, where occasional fair behaviors
(
∼
5
%
)
are sufficient to drive the whole population to behave in the half–half split manner. We also develop a mean-field theory, which correctly reproduces the first-order phase transition and points out the reason. Heterogeneously structured populations, however, display continuous fairness transition; surprisingly, very few hub nodes acting as fair players are able to entrain the whole population to the full fairness state. Our results thus reveal the unexpected strength of ‘good Samaritans’, which may constitute a new explanation for the emergence of fairness in our society.
Funder
National Natural Science Foundation of China
Central University Basic Research Fund of China
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems
Cited by
3 articles.
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