Adversarial Risk Analysis as a Decomposition Method for Structured Expert Judgement Modelling

David Ríos Insua (), David Banks, Jesús Ríos and Jorge González-Ortega
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David Ríos Insua: Instituto de Ciencias Matemáticas (CSIC-UAM-UC3M-UCM)
David Banks: Department of Statistical Science (Duke University)
Jesús Ríos: IBM Research Division (IBM)
Jorge González-Ortega: Instituto de Ciencias Matemáticas (CSIC-UAM-UC3M-UCM)

Chapter Chapter 7 in Expert Judgement in Risk and Decision Analysis, 2021, pp 179-196 from Springer

Abstract: Abstract We argue that adversarial risk analysis may be incorporated into the structured expert judgement modelling toolkit for cases in which we need to forecast the actions of competitors based on expert knowledge. This is relevant in areas such as cybersecurity, security, defence and business competition. As a consequence, we present a structured approach to facilitate the elicitation of probabilities over the actions of other intelligent agents by decomposing them into multiple, but simpler, assessments later combined together using a rationality model of the adversary to produce a final probabilistic forecast. We then illustrate key concepts and modelling strategies of this approach to support its implementation.

Keywords: Structured expert judgement; Adversarial risk analysis; Decomposition; Security; Cybersecurity (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-46474-5_7

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DOI: 10.1007/978-3-030-46474-5_7

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