人口的进化动态 游戏与基于愿望的学习规则规则
IEEE transactions on neural networks and learning systems
|August 30, 2024
概括
一个新的基于愿望的学习规则",满意-合作,不满意-缺陷",促进了代理人群中的合作. 这一规则在各种人口结构中是有效的,甚至在囚犯困境游戏 (PDG) 中超过了其他基于愿望的方法.
科学领域:
- 进化游戏理论 进化游戏理论
- 基于代理的建模模型
- 行为经济学是一种行为经济学.
背景情况:
- 游戏理论中的代理人根据回报和愿望调整战略.
- 基于愿望的学习规则对于理解竞争性代理种群的进化动态至关重要.
- 愿望影响学习规则和合作的具体机制仍然是研究领域.
研究的目的:
- 提出和分析一种新的基于愿望的学习规则:"满意-合作,不满意-缺陷.
- 确定这项新规则在哪些条件下可以促进两人游戏中的合作.
- 将这个规则的有效性与其他基于愿望的学习规则进行比较,特别是囚犯困境游戏 (PDG).
主要方法:
- 在代理群体中引入"满意-合作,不满意-缺陷"学习规则.
- 在有限的混合,无限的混合和弱选择下结构化的群体中有利于合作的条件的数学推导.
- 数字计算和计算机模拟,特别用于囚犯困境游戏 (PDG).
主要成果:
- 在有限的混合,无限的混合和结构化的群体中,无论不同的愿望水平如何,都发现了增加合作的相同数学条件.
- 理论预测得到了数字和PDG模拟结果的强有力的支持.
- 拟议的"满意-合作,不满意-缺陷"学习规则显示,与基于愿望的学习规则相比,在PDG中促进合作的能力更大.
结论:
- "满意-合作,不满意-缺陷"的学习规则提供了一个可行的机制,以促进不同的人口结构的合作.
- 基于愿望的学习,当有效地设计时,可以成为进化游戏理论中合作行为的强大驱动力.
- 这项研究提供了一种新的视角,对愿望在塑造社会行为和促进合作的作用,在基于代理的系统.
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