在公共产品博弈中通过概率惩罚和环境反馈促进合作进化

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-10-28 DOI:10.1016/j.chaos.2024.115693
Jiaqi Liu, Qianwei Zhang, Rui Tang
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引用次数: 0

摘要

惩罚自私的个体被认为是维持社会合作的有效方法。实际上,相应的惩罚概率应随不同的博弈环境而变化。然而,目前大多数研究都将这种概率视为常数或外生给定。本文以公共物品博弈为基础,设计了一种环境反馈机制,并建立了一个反馈演化博弈模型。该模型假设惩罚叛逃者的概率会随着合作者比例的变化而变化,最终影响个体决策。通过理论分析和数值模拟,我们得到了系统在不同参数条件下的三种稳定状态:低惩罚概率的完全叛逃状态、高惩罚概率的完全合作状态和双稳态。我们的研究结果表明,环境反馈机制在促进社会长期稳定和可持续发展方面发挥着至关重要的作用。
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Fostering cooperative evolution through probabilistic punishment and environmental feedback in public goods game
Punishing selfish individuals is regarded as an effective method to maintain social cooperation. In reality, the corresponding punishment probability should vary with different game environments. However, most current research treats this probability as a constant or exogenously given. In this paper, based on the public goods game, we design an environmental feedback mechanism and establish a feedback evolutionary game model. The model assumes that the probability of punishing defectors will change with the proportion of cooperators, ultimately influencing individual decision-making. Through theoretical analysis and numerical simulations, we obtain three stable states of the system under different parameter conditions: a state of complete defection with low punishment probability, a state of complete cooperation with high punishment probability, and a bistable state. Our research results indicate that the environmental feedback mechanism plays a crucial role in promoting long-term social stability and sustainable development.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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