复杂网络中异质性投资对信任演化的影响

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Enqiang Zhu , Jia Chen , Shiqi Liu , Xiaokai Zhang , Chanjuan Liu
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引用次数: 0

摘要

合作,尽管与达尔文的竞争理论有明显的矛盾,但却是普遍存在的。信任是社会经济互动和促进合作的基础,但过度信任可能导致损失。此外,信任博弈研究表明,异质性、声誉和惩罚显著促进了合作。然而,传统模型通常假设固定的投资者投资,忽略了适应性决策。为了解决这一限制,我们开发了一个包含投资异质性的多代理信任博弈。在该框架下,投资者根据集体信任水平动态调整其出资,使高信任群体积累更大的总资产。模拟结果显示了三个主要发现:(1)异质投资加速了信托的发展,扩大了可信赖的受托人和投资者的数量,同时增加了总资产;(2)在较强的社会困境下,投资异质性的增加促进了高信任均衡;(3)战略个体比例对稳定信任水平的影响可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The influence of heterogeneous investment on the evolution of trust in complex networks
Cooperation, despite its apparent contradiction with Darwinian competition, is widespread. Trust underpins socio-economic interactions and promotes cooperation, yet excessive trust can lead to losses. Furthermore, trust game studies indicate that heterogeneity, reputation, and punishment significantly enhance cooperation. However, traditional models often assume fixed investor investments, overlooking adaptive decision-making. To address this limitation, we develop a multi-agent trust game incorporating investment heterogeneity. In this framework, investors dynamically adjust their contributions based on collective trust levels, enabling high-trust groups to accumulate greater total assets. Simulation results demonstrate three key findings: (1) Heterogeneous investments accelerate the development of trust, expanding the populations of trustworthy trustees and investors while increasing total assets; (2) Increased investment heterogeneity facilitates high-trust equilibria even under strong social dilemmas; (3) The proportion of strategic individuals has a negligible impact on stabilized trust levels.
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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