反事实归因的动态在空间公共产品游戏中对遗憾最小化感到遗憾
1Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka 816-8580, Japan.
Chaos (Woodbury, N.Y.)
|December 8, 2025
概括
一个新的模型,反事实归因遗憾最小化 (CARM),解释了空间游戏中的合作. 它使用诸如遗憾之类的认知过程来显示动态的战略转变,与旧模型中的静态集群不同.
科学领域:
- 进化游戏理论 进化游戏理论
- 计算社会科学 计算社会科学
- 认知科学 认知科学
背景情况:
- 空间公共产品游戏是理解合作演变的关键.
- 当前的模型经常使用社会模仿或强化学习,忽视了人类的认知过程.
- 需要更现实的方法来捕捉合作动态中复杂的决策.
研究的目的:
- 引入一种新的战略更新机制,即反事实归因遗憾最小化 (CARM).
- 在进化游戏中更好地模拟人类决策背后的认知过程.
- 探索在这种新机制下出现的集体行为和稳定性.
主要方法:
- 开发了基于遗憾积累和遗憾匹配的CARM.
- 整合了三个心理权重:可访问性,因果归因和情绪反应.
- 进行了广泛的蒙特卡洛模拟和灵敏度分析.
主要成果:
- 卡姆产生多样化的集体行为:吸收状态,稳定的共存,和双稳定的振荡.
- 认知参数显著影响合作值,稳定状态水平和动态稳定性.
- 宏观的共存是通过振荡的个人策略来维持的,而不是静态的集群.
结论:
- 卡姆为空间游戏中的合作动态提供了更具认知可信的解释.
- 该模型强调了动态的个人战略转移在维持合作中的作用.
- 这项工作为研究合作的出现和可持续性提供了新的框架.
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