在合作的动态多重网络中,关系和相互作用的共同演变
Xiaojin Xiong1, Ziyan Zeng1, Minyu Feng1
1The College of Artificial Intelligence, Southwest University, No.2 Tiansheng Road, Beibei, Chongqing 400715, China.
Chaos (Woodbury, N.Y.)
|February 16, 2024
概括
社会关系的动态影响合作. 多重网络中的共同进化模型表明,更高的网络连接性有助于合作,但强大的关系适应性链接阻碍了合作. 关系的两极化与合作水平有关.
科学领域:
- 复杂的系统复杂的系统.
- 社交网络分析 社交网络分析
- 游戏理论 游戏理论
背景情况:
- 社会互动塑造个人关系和合作.
- 多重网络提供了一个框架来建模动态的社会结构.
- 互动回报与关系强度之间的相互作用对于理解合作至关重要.
研究的目的:
- 在多重网络模型中研究社会关系和合作的共同演变.
- 探索网络拓以及关系强度和适应性之间的合如何影响合作动态.
- 分析关系指数分布与合作的普遍性之间的关系.
主要方法:
- 在多重网络上开发了一个共进化的模型,具有两个层:交互和关系.
- 在交互层模拟了弱囚犯的困境游戏,回报影响了关系权重.
- 将关系索引纳入玩家健身,以及游戏回报,并分析了不同的关系层拓.
主要成果:
- 关系层中较高的平均度通常会促进正则图中的合作.
- 网络随机性对于在具有挑战性的条件下进行合作至关重要.
- 发现关系指数和健康之间更强的合阻碍了合作的演变.
结论:
- 网络结构和关系和健康之间的反循环显著影响合作.
- 这些发现凸显了在不断发展的社交网络中管理合作的复杂动态.
- 关系指数两极化作为总体人口合作水平的指标.
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