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Updated: Jun 27, 2025

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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在多代理主动推理中的共同抗议
Mahault Albarracin1,2, Riddhi J Pitliya1,3, Toby St Clere Smithe1,4
1VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA.
Entropy (Basel, Switzerland)
|April 26, 2024
概括
这项研究结合了现象学,主动推理和类别理论,以建模具有共同目标的社会行动. 它通过共享的特点将共同的目标正式化,解释在复杂环境中群体的意向性和协调.
科学领域:
- 跨学科的研究结合现象学,理论生物学 (主动推理) 和数学 (类别理论).
- 专注于理解社会行动和集体行为的理论框架.
背景情况:
- 哈塞尔的现象学提供了对内在时间意识 (保留,原始印象,延续) 的洞察.
- 主动推理为使用变量贝叶斯推理的代理行为建模提供了正式框架.
- 分类理论,特别是sheaf和topos理论,为建模复杂系统提供了先进的数学工具.
研究的目的:
- 开发一个全面的框架来理解基于共同目标的社会行动.
- 通过共同的突出来正式确定共同的目标,并探索群体意向的出现.
- 在随机环境中数学建模个人和群体的相互作用.
主要方法:
- 哈塞尔的现象学和主动推理原则的概述.
- 将共享的突起与主动推理的共享生成模型集成.
- 运用sheaf和topos理论对代理互动和世界观的数学表示.
- 使用代理模型的多项式表示之间的形态.
主要成果:
- 一个统一的框架,将现象学,主动推理和社会行动的类别理论联系在一起.
- 将共同的目标正式化为共同的愿望,阐明团体的意向.
- 使用sheaf和topos理论对代理互动和共识进行数学建模.
- 确定共同的突出点对于协调和实现共同目标至关重要.
结论:
- 综合框架为理解集体目标导向行为提供了一种新的方法.
- 共享的突起是促进群体协调的关键新兴属性.
- 承认在实现共同目标时,随机性和不确定性所带来的挑战.
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