相关实验视频
Updated: Jul 24, 2025

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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具有不同认知架构的代理人的政策中的共识问题
Damian Radosław Sowinski1, Jonathan Carroll-Nellenback2, Jeremy DeSilva3
1Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA.
Entropy (Basel, Switzerland)
|July 8, 2023
概括
即使使用相同的数据,具有不同认知架构的代理人也可能得出不同的结论,这阻碍了信息共享人群的共识. 这挑战了政体中的集体决策.
科学领域:
- 人工智能的人工智能
- 认知科学 认知科学
- 社会学 社会学 社会学
背景情况:
- 代理人根据有限的数据和内部认知架构做出决策.
- 数据采样和内存存储的变化会影响代理人的结论和行动.
- 信息共享对于政权 (代理人人口) 来说至关重要.
研究的目的:
- 调查异质认知架构对政体共识的影响.
- 证明即使在理想条件下也可能无法达成共识.
- 分析基于代理的系统中的"共识问题".
主要方法:
- 在具有已知的环境动态的政体的玩具模型中分析转移.
- 对具有未知的环境动态的经验气候数据流的检查.
主要成果:
- 不同质的认知架构可以阻止各方在数据流的结论上达成共识.
- "共识问题"在模拟和现实数据中得到了证明.
结论:
- 认知多样性可能是代理人群体中集体协议的根本障碍.
- 了解代理人认知对于设计有效的信息共享系统和预测社会结果至关重要.
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