通过捐赠和道德情感探索生物和社会系统的合作进化

IF 2 4区 生物学 Q2 BIOLOGY
Jianyu Pu, Jiqin Li
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引用次数: 0

摘要

本研究探讨捐赠机制和道德情绪如何影响生物系统和社会系统的合作演化。利用进化博弈论框架,我们建立了一个个体可以合作或背叛的空间系统模型,研究了资源从富裕个体到贫穷个体的转移如何塑造合作动态。我们引入了一个道德情绪参数,赋予合作者内在的心理利益,抵消了捐赠成本,提高了他们的整体适合度。我们的研究结果表明,适度的捐赠水平显著地稳定了合作,特别是在有强烈的背叛动机的环境中。此外,道德情操通过使捐赠更具可持续性来支持合作策略。捐赠和道德情感之间的相互作用产生非线性效应,它们的共同影响比单独一个因素更有效地促进合作。此外,我们还分析了合作的空间扩散,表明道德情绪在维持和扩展网络中的合作行为中起着至关重要的作用。这些见解有助于更深入地了解社会和道德因素如何影响合作,对自然和人类社区都有影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring cooperation evolution in biological and social systems through donation and moral sentiment
This study explores how donation mechanisms and moral sentiment influence the evolution of cooperation in biological and social systems. Using an evolutionary game theory framework, we model a spatial system where individuals can either cooperate or defect, examining how resource transfers from wealthier to poorer individuals shape cooperative dynamics. We introduce a moral sentiment parameter that grants cooperators intrinsic psychological benefits, offsetting the cost of donation and enhancing their overall fitness. Our findings reveal that moderate donation levels significantly stabilize cooperation, particularly in environments with strong incentives to defect. Moreover, moral sentiment bolsters cooperative strategies by making donation more sustainable. The interplay between donation and moral sentiment produces a nonlinear effect, where their combined influence promotes cooperation more effectively than either factor alone. Additionally, we analyze the spatial spread of cooperation, showing that moral sentiment plays a crucial role in maintaining and expanding cooperative behavior across a network. These insights contribute to a deeper understanding of how social and moral factors shape cooperation, with implications for both natural and human communities.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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