Explainable AI for Operational Research: a defining framework, methods, applications, and a research agenda
| dc.coverage | DOI: 10.1016/j.ejor.2023.09.026 | |
| dc.creator | De Bock, Koen W. | |
| dc.creator | Coussement, Kristof | |
| dc.creator | Caigny, Arno De | |
| dc.creator | Słowiński, Roman | |
| dc.creator | Baesens, Bart | |
| dc.creator | Boute, Robert N. | |
| dc.creator | Choi, Tsan Ming | |
| dc.creator | Delen, Dursun | |
| dc.creator | Kraus, Mathias | |
| dc.creator | Lessmann, Stefan | |
| dc.creator | Maldonado, Sebastián | |
| dc.creator | Martens, David | |
| dc.creator | Óskarsdóttir, María | |
| dc.creator | Vairetti, Carla | |
| dc.creator | Verbeke, Wouter | |
| dc.creator | Weber, Richard | |
| dc.date | 2024 | |
| dc.date.accessioned | 2026-01-05T21:21:05Z | |
| dc.date.available | 2026-01-05T21:21:05Z | |
| dc.description | <p>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.</p> | eng |
| dc.identifier | https://investigadores.uandes.cl/en/publications/02a2e80b-2807-49a5-afaa-5df3ea718aac | |
| dc.identifier.uri | https://repositorio.uandes.cl/handle/uandes/69263 | |
| dc.language | eng | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.source | vol.317 (2024) nr.2 p.249-272 | |
| dc.subject | Decision analysis | |
| dc.subject | Explainable artificial intelligence | |
| dc.subject | Interpretable machine learning | |
| dc.subject | XAI | |
| dc.subject | XAIOR | |
| dc.title | Explainable AI for Operational Research: a defining framework, methods, applications, and a research agenda | eng |
| dc.type | Review article | eng |
| dc.type | Artículo de revisión | spa |