相关实验视频
Updated: Jun 7, 2025

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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在参与式预算中赋予少数群体和所有人的权力:基于代理人的建模视角
Dino Carpentras1, Regula Hänggli Fricker2, Dirk Helbing1,3
1ETH Zurich, Zurich, Switzerland.
概括
结合集体智能 (CI) 和参与式预算 (PB) 可以改善公民的决策. 使用共同知识库的开放创新方法提高了所有群体的公平性和解决方案质量.
科学领域:
- 计算社会科学 计算社会科学
- 政治科学 政治科学是指政治学.
- 人工智能的人工智能
背景情况:
- 人们对公民参与政治决策日益感兴趣.
- 参与式预算 (PB) 使公民有能力提出和资助项目.
- 集体智能 (CI) 突出了群体解决问题的能力.
研究的目的:
- 调查CI和PB之间的协同作用,以公民为主导的问题识别和解决方案的产生.
- 解决 CI-PB 综合系统中潜在的公平性问题.
- 通过包容性方法提高整体解决方案质量.
主要方法:
- 基于代理的建模来模拟结合的CI和PB系统.
- 基于集团规模的解决方案质量和公平性的分析.
- 引入一个共同的知识库,以促进信息共享.
主要成果:
- 最初的CI-PB模型可以惩罚少数群体,当解决方案质量取决于群体规模时.
- 一个共同的知识库通过利用多数人的贡献来提高少数解决方案的质量.
- 这种共享知识方法提高了多数解决方案的质量,为所有人带来了更好的结果.
结论:
- 整合CI和PB为公民参与治理提供了一个强大的框架.
- 在参与式系统中,共同的知识库对于确保公平性和提高解决方案质量至关重要.
- 开放式创新和信息共享对于共同创造更美好的城市未来至关重要.
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