title: Fairness emergence from zero-intelligence agents.
abstract: Fairness plays a key role in explaining the emergence and maintenance of cooperation. Opponent-oriented social utility models were often proposed to explain the origins of fairness preferences in which agents take into account not only their own outcomes but are also concerned with the outcomes of their opponents. Here, we propose a payoff-oriented mechanism in which agents update their beliefs only based on the payoff signals of the previous ultimatum game, regardless of the behaviors and outcomes of the opponents themselves. Employing adaptive ultimatum game, we show that (1) fairness behaviors can emerge out even under such minimalist assumptions, provided that agents are capable of responding to their payoff signals, (2) the average game payoff per agent per round decreases with the increasing discrepancy rate between the average giving rate and the average asking rate, and (3) the belief update process will lead to 50%-50% fair split provided that there is no mutation in the evolutionary dynamics.
authors.affiliation: School of Business Administration, Zhejiang Normal University, Jinhua 321004, People's Republic of China.
authors.forename: Wen-Qi
authors.initials: WQ
authors.lastname: Duan
authors.forename: H Eugene
authors.initials: HE
authors.lastname: Stanley
mesh_terms: D005075:Biological Evolution; D005716:Game Theory; D007360:Intelligence; D012935:Social Justice