Evolutionary dynamics in stochastic nonlinear public goods games

Wenqiang Zhu, Xin Wang, Chaoqian Wang, Longzhao Liu, Jiaxin Hu, Zhiming Zheng, Shaoting Tang, Hongwei Zheng, Jin Dong
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Abstract

Understanding the evolution of cooperation in multiplayer games is of vital significance for natural and social systems. An important challenge is that group interactions often leads to nonlinear synergistic effects. However, previous models mainly focus on deterministic nonlinearity where the arise of synergy or discounting effect is determined by certain conditions, ignoring uncertainty and stochasticity in real-world systems. Here, we develop a probabilistic framework to study the cooperative behavior in stochastic nonlinear public goods games. Through both analytical treatment and Monte Carlo simulations, we provide comprehensive understanding of social dilemmas with stochastic nonlinearity in both well-mixed and structured populations. We find that increasing the degree of nonlinearity makes synergy more advantageous when competing with discounting, thereby promoting cooperation. Interestingly, we show that network reciprocity loses effectiveness when the probability of synergy is small. Moreover, group size exhibits nonlinear effects on group cooperation regardless of the underlying structure. Our findings thus provide novel insights into how stochastic nonlinearity influences the emergence of prosocial behavior.
随机非线性公共产品博弈中的进化动力学
了解多人游戏中的合作演化对自然和社会系统至关重要。一个重要的挑战是,群体互动往往会导致非线性协同效应。然而,以往的模型主要关注确定性非线性,即协同效应或折扣效应的产生是由特定条件决定的,忽略了现实世界系统中的不确定性和随机性。在这里,我们建立了一个研究随机非线性公共物品博弈中合作行为的反概率框架。通过分析处理和蒙特卡洛模拟,我们全面了解了在混合良好的人群和结构化人群中具有随机非线性的社会困境。我们发现,增加非线性程度会使协同作用在贴现竞争中更具优势,从而促进合作。有趣的是,我们发现当协同作用的概率很小时,网络互惠就会失去效力。此外,无论基础结构如何,群体规模都会对群体合作产生非线性影响。因此,我们的发现为随机非线性如何影响社会行为的出现提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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