Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda
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Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier B.V.
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The ability to understand and explain the outcomes of data analysis methods, with regard to aiding decision-making, has become a critical requirement for many applications. For example, in operational research domains, data analytics have long been promoted as a way to enhance decision-making. This study proposes a comprehensive, normative framework to define explainable artificial intelligence (XAI) for operational research (XAIOR) as a reconciliation of three subdimensions that constitute its requirements: performance, attributable, and responsible analytics. In turn, this article offers in-depth overviews of how XAIOR can be deployed through various methods with respect to distinct domains and applications. Finally, an agenda for future XAIOR research is defined. © 2023 Elsevier B.V.
Açıklama
Anahtar Kelimeler
Decision Analysis, Explainable Artificial İntelligence, Interpretable Machine Learning, Xaı, Xaıor
Kaynak
European Journal of Operational Research
WoS Q Değeri
Scopus Q Değeri
Q1
