弱选择下混合博弈中的策略优势。

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-09-01 DOI:10.1063/5.0290642
Yu Chen, Bin-Quan Li
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引用次数: 0

摘要

尽管在非结构化种群中,自然选择系统地倾向于叛逆者而不是合作者,但在结构化种群中,进化动力学显示出更大的复杂性。此外,多博弈环境已经成为进化博弈理论的一个重要前沿。虽然之前的研究主要集中在静态的单一游戏场景,但现在越来越多的学者关注混合游戏框架,以更好地捕捉现实世界互动的动态异质性。这项工作研究了由两种游戏类型组成的混合游戏中的策略优势,检查了固定和随机变化的游戏混合。通过严格的数学分析和计算模拟,我们建立了在弱选择条件下,策略优势的判据等同于平均单个博弈的判据。这种等价性为简化复杂的多博弈互动提供了统一的框架,并促进了对结构化群体合作进化的机制理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strategy dominance in mixed games under weak selection.

Although natural selection systematically favors defectors over cooperators in unstructured populations, evolutionary dynamics in structured populations reveal substantially greater complexity. Moreover, multi-game environments have emerged as a critical frontier in evolutionary game theory. Whereas prior research predominantly focused on static single-game scenarios, growing scholarly attention now addresses mixed-game frameworks that better capture the dynamical heterogeneity of real-world interactions. This work investigates strategy dominance in mixed games comprising two game types, examining both fixed and stochastically varying game mixtures. Through rigorous mathematical analysis and computational simulations, we establish that under weak selection conditions, the criterion for strategy dominance is equivalent to that of an average single game. This equivalence provides a unifying framework for simplifying complex multi-game interactions and advances mechanistic understanding of cooperation evolution in structured populations.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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