根据它们的关键性质来定义不确定性下决策问题的分析复杂性
Alexander Gutfraind1,2,3
1Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, Illinois, United States of America.
PeerJ. Computer science
|August 15, 2024
概括
本研究引入了决策分析中分析复杂性的定量得分. 它识别了诸如可逆性的问题属性,这些属性在不确定性下简化了解决方案.
科学领域:
- 决策分析 决策分析
- 风险管理 风险管理
- 复杂性科学 复杂性科学
背景情况:
- 不确定性在决策分析和风险管理中构成了重大挑战.
- 不太了解的问题导致概率估计的高变化和偏差.
- 现有的文献缺乏对分析复杂性的量化衡量.
研究的目的:
- 开发一个分析复杂性的定量得分.
- 确定减轻不确定性的决策问题的属性.
- 建立在以前的不确定性等级体系之上.
主要方法:
- 审查了90多种应对不确定性的策略.
- 包括专家决策者 (工程师,军事规划者) 使用的方法.
- 分析的属性,使问题解决,尽管不确定性.
主要成果:
- 确定了诸如小动作空间和可逆性等关键性质.
- 这些特性使得即使在高不确定性的情况下,问题也能得到解决.
- 根据这些属性的可用性定义了分析复杂度得分.
结论:
- 可以定义分析复杂性的定量得分.
- 像可逆性这样的问题属性是简化不确定性下复杂决策的关键.
- 这一分数有助于决策分析和风险管理.
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