Forecasting adversarial actions using judgment decomposition-recomposition

Ministerio de Ciencia e Innovación (España)

Detalles Bibliográficos
Autores: Gómez, Yolanda, Rios, Jesus, Rios Insua, David, Vila, José
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/422638
Acceso en línea:http://hdl.handle.net/10261/422638
https://api.elsevier.com/content/abstract/scopus_id/85189663904
Access Level:acceso abierto
Palabra clave:Adversarial risk analysis
Behavioural experiments
Decision analysis
Discrete choice models
Structured expert judgment
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spelling Forecasting adversarial actions using judgment decomposition-recompositionGómez, YolandaRios, JesusRios Insua, DavidVila, JoséAdversarial risk analysisBehavioural experimentsDecision analysisDiscrete choice modelsStructured expert judgmentMinisterio de Ciencia e Innovación (España)[Data and code availability] The code and data necessary to reproduce the results presented in the paper have been made available at the following link: https://zenodo.org/records/10843496In 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.Research supported by the EU’s Horizon 2020 project 740920 CYBECO. David Rios Inusa is grateful to PID2021-124662OB-I00 from the Ministry of Science and Technology, the AXA-ICMAT Chair in Adversarial Risk Analysis and EOARD (FA8655-21-1-7042) and AFOSR (FA-9550-21-1-0239) projects. This work was partially supported by the NSF under Grant DMS-1638521 to the SAMSI and a BBVA Foundation (AMALFI project). Jose Vila is grateful to the financial support by the Generalitat Valenciana under the PROMETEO CIPROM/2022/029 program and project PID2021-127946OB-I00 funded by the MCIN as well as UE-FEDER.NoElsevierGómez, Yolanda [0000-0002-4008-9084]Vila, José [0000-0002-5841-1115]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Preprintinfo:eu-repo/semantics/submittedVersionapplication/pdfhttp://hdl.handle.net/10261/422638https://api.elsevier.com/content/abstract/scopus_id/85189663904reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.ijforecast.2024.03.004https://doi.org/10.1016/j.ijforecast.2024.03.004Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4226382026-05-22T06:33:51Z
dc.title.none.fl_str_mv Forecasting adversarial actions using judgment decomposition-recomposition
title Forecasting adversarial actions using judgment decomposition-recomposition
spellingShingle Forecasting adversarial actions using judgment decomposition-recomposition
Gómez, Yolanda
Adversarial risk analysis
Behavioural experiments
Decision analysis
Discrete choice models
Structured expert judgment
title_short Forecasting adversarial actions using judgment decomposition-recomposition
title_full Forecasting adversarial actions using judgment decomposition-recomposition
title_fullStr Forecasting adversarial actions using judgment decomposition-recomposition
title_full_unstemmed Forecasting adversarial actions using judgment decomposition-recomposition
title_sort Forecasting adversarial actions using judgment decomposition-recomposition
dc.creator.none.fl_str_mv Gómez, Yolanda
Rios, Jesus
Rios Insua, David
Vila, José
author Gómez, Yolanda
author_facet Gómez, Yolanda
Rios, Jesus
Rios Insua, David
Vila, José
author_role author
author2 Rios, Jesus
Rios Insua, David
Vila, José
author2_role author
author
author
dc.contributor.none.fl_str_mv Gómez, Yolanda [0000-0002-4008-9084]
Vila, José [0000-0002-5841-1115]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Adversarial risk analysis
Behavioural experiments
Decision analysis
Discrete choice models
Structured expert judgment
topic Adversarial risk analysis
Behavioural experiments
Decision analysis
Discrete choice models
Structured expert judgment
description Ministerio de Ciencia e Innovación (España)
publishDate 2025
dc.date.none.fl_str_mv 2025
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Preprint
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/422638
https://api.elsevier.com/content/abstract/scopus_id/85189663904
url http://hdl.handle.net/10261/422638
https://api.elsevier.com/content/abstract/scopus_id/85189663904
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.ijforecast.2024.03.004
https://doi.org/10.1016/j.ijforecast.2024.03.004
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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