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社会学习具有复杂的传染性
Hiroaki Chiba-Okabe1,2, Joshua B Plotkin1,2,3
1Program in Applied Mathematics & Computational Science, University of Pennsylvania, Philadelphia, PA 19104.
概括
社会行为通过复杂的传染传播,需要多次暴露才能被采用. 这个新模型将简单的模仿与复杂的传染结合在一起,改变了经典游戏理论场景中的结果.
科学领域:
- 进化游戏理论 进化游戏理论
- 社会学习的动态 社会学习的动态
- 复杂系统建模 复杂系统建模
背景情况:
- 传统的社会学习模型假设简单的传染,其中一个互动足以模仿.
- 现实世界的行为传播通常涉及复杂的传染,需要多次暴露才能被采用.
- 现有的模型可能无法完全捕捉社交网络中行为变化的细微差别.
研究的目的:
- 引入一种新的框架,将简单的利偏见模仿与复杂的传染结合起来.
- 模拟社会行为在人口中传播的现实传染动态.
- 分析复杂传染对进化游戏理论结果的影响.
主要方法:
- 为社会学习制定了一个离散的时间和状态随机过程.
- 导出连续极限作为一个普通微分方程,概括复制器方程.
- 将模型应用于线性频率依赖的游戏,包括囚犯困境,雪流和协调游戏.
主要成果:
- 与传统模仿相比,复杂的传染动力产生质量上不同的结果.
- 囚犯的困境可以从一个所有缺陷的平衡转移到一个混合或可二元化的系统.
- 雪地漂流和协调游戏在复杂的传染下表现出改变的平衡结构.
- 结果取决于传染复杂性和选择强度之间的相互作用.
结论:
- 该框架提供了一种综合方法来理解社会系统中现实的行为变化.
- 整合复杂的传染提供了更细致的社会学习和其进化后果的视角.
- 这项工作将进化游戏理论和复杂的传染联系联系起来,使其具有更广泛的适用性.
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