The reputation-based reward mechanism promotes the evolution of fairness

被引:1
作者
Deng, Lili [1 ]
Wang, Rugen [1 ]
Liao, Ying [1 ]
Xu, Ronghua [1 ]
Wang, Cheng [2 ,3 ]
机构
[1] Zhejiang Univ Technol, Sch Management, Hangzhou 310023, Peoples R China
[2] Zhejiang Univ Technol, Coll Mech Engn, Hangzhou 310023, Peoples R China
[3] Zhejiang Univ Technol, Taizhou Res Inst, Taizhou Key Lab Adv Mfg Technol, Taizhou 318000, Peoples R China
基金
中国国家自然科学基金;
关键词
Reputation; Reward; Fairness; Ultimatum game; PUBLIC-GOODS GAME; ULTIMATUM; COOPERATION; DYNAMICS; BEHAVIOR;
D O I
10.1016/j.amc.2024.129042
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In real life, a good reputation generally brings positive returns to individuals. For example, merchants with numerous good reviews usually gain higher profits. Considering this in the ultimatum game, we propose a reputation-based reward mechanism to investigate the evolution of fairness. Specifically, individuals' reputations evolve dynamically based on the outcomes of games. At the same time, we set a reputation threshold in the population. When individuals' reputations exceed the reputation threshold, they are considered excellent. Otherwise, they are ordinary. The excellent individuals can receive extra rewards compared to the ordinary ones. Finally, individuals' total payoffs determine their fitness within the population. Based on these settings, this paper mainly explores how reputation threshold, weight factor and reward strength affect the evolution of fairness. Through a series of simulations, the reputation-based rewards mechanism is proved to effectively promote the fairness in the population. To be specific, we find that higher reputation thresholds and smaller values of weight factor significantly enhance the promotion effect of reward on fairness. Simultaneously, there is a specific correspondence between the reputation threshold and the weight factor. When reward strength is fixed, for different reputation thresholds, the optimal value of weight factor to achieve maximum fairness levels also varies. Additionally, increasing reward strength can significantly promote fairness.
引用
收藏
页数:13
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