Literature DB >> 20365628

Fairness emergence from zero-intelligence agents.

Wen-Qi Duan1, H Eugene Stanley.   

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.

Entities:  

Mesh:

Year:  2010        PMID: 20365628     DOI: 10.1103/PhysRevE.81.026104

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  Random allocation of pies promotes the evolution of fairness in the Ultimatum Game.

Authors:  Xiaofeng Wang; Xiaojie Chen; Long Wang
Journal:  Sci Rep       Date:  2014-04-01       Impact factor: 4.379

2.  Fair Topologies: Community Structures and Network Hubs Drive Emergence of Fairness Norms.

Authors:  Mohsen Mosleh; Babak Heydari
Journal:  Sci Rep       Date:  2017-06-02       Impact factor: 4.379

3.  Adaptive role switching promotes fairness in networked ultimatum game.

Authors:  Te Wu; Feng Fu; Yanling Zhang; Long Wang
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

  3 in total

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