让我们让一个人回到网络物理社会研究:公共心理模型框架
Mare Teichmann1, Jaanus Kaugerand1, Merik Meriste1
1Laboratory for Proactive Technologies, Department of Software Science, Tallinn University of Technology, Tallinn, Estonia.
Frontiers in neuroergonomics
|December 12, 2025
概括
本研究介绍了公共心理模型框架 (PMMF),用于预测和影响危急情况下的公共行为. PMMF将心理模型,情境意识和压力管理联系起来,以改善决策和人工智能协作.
科学领域:
- 认知科学 认知科学
- 网络物理社会系统 (CPSS)
- 人与人工智能的互动
背景情况:
- 了解危急情况中的公众行为对于有效干预至关重要.
- 现有的情境意识模型缺乏对决策的解释机制的关注.
- 复杂的网络物理社会系统 (CPSS) 需要综合的行为分析方法.
研究的目的:
- 介绍公共心理模型框架 (PMMF) 用于分析和预测公共行为.
- 建立心理模型,行为,情境意识和压力管理之间的联系.
- 在关键场景中增强自适应性决策和人-人工智能协作.
主要方法:
- 开发了公共心理模型框架 (PMMF).
- 分析了塑造多个层面感知和行为的内部和外部指标.
- 集成PMMF与动机-机会-能力 (MOA) 理论进行行为评估.
主要成果:
- 在关键情况下,PMMF提供了一种系统的方法来预测和影响公众的行为.
- 确定了行为偏差和压力下稳定性的触发因素和标记.
- 证明了PMMF在评估CPSS中的行为潜力和表现方面的实用性.
结论:
- 在CPSS中,PMMF为理解意义构造和决策提供了一种新的方法.
- 该框架支持针对复杂社会技术环境的有针对性的干预措施和以弹性为导向的设计.
- 与MOA理论的整合加强了神经机能学评估和道德行为设计.
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