Forecasting adversarial actions using judgment decomposition-recomposition

IF 6.9 2区 经济学 Q1 ECONOMICS
Yolanda Gomez , Jesus Rios , David Rios Insua , Jose Vila
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引用次数: 0

Abstract

In domains such as homeland security, cybersecurity, and competitive marketing, it is frequently the case that analysts need to forecast actions by other intelligent agents that impact the problem of interest. Standard structured expert judgment elicitation techniques may fall short in this type of problem as they do not explicitly take into account intentionality. We present a decomposition technique based on adversarial risk analysis followed by a behavioural recomposition using discrete choice models that facilitate such elicitation process and illustrate its reasonable performance through behavioural experiments.
利用判断分解-重组预测对抗行动
在国土安全、网络安全和竞争营销等领域,分析人员经常需要预测其他智能代理对相关问题的影响。标准的结构化专家判断征询技术可能无法解决这类问题,因为它们没有明确考虑到意图性。我们提出了一种基于对抗性风险分析的分解技术,然后利用离散选择模型进行行为再分解,从而促进了这种诱导过程,并通过行为实验说明了其合理性能。
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来源期刊
CiteScore
17.10
自引率
11.40%
发文量
189
审稿时长
77 days
期刊介绍: The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.
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