dc.creator | Borrego Díaz, Joaquín | es |
dc.creator | Galán Páez, Juan | es |
dc.date.accessioned | 2022-06-30T08:30:23Z | |
dc.date.available | 2022-06-30T08:30:23Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Borrego Díaz, J. y Galán Páez, J. (2022). Knowledge representation for explainable artificial intelligence: modeling foundations from complex systems. Complex and Intelligent Systems, 8 (2), 1579-1601. | |
dc.identifier.issn | 2199-4536 | es |
dc.identifier.uri | https://hdl.handle.net/11441/134822 | |
dc.description.abstract | Alongside the particular need to explain the behavior of black box artificial intelligence (AI) systems, there is a general need
to explain the behavior of any type of AI-based system (the explainable AI, XAI) or complex system that integrates this type
of technology, due to the importance of its economic, political or industrial rights impact. The unstoppable development of
AI-based applications in sensitive areas has led to what could be seen, from a formal and philosophical point of view, as
some sort of crisis in the foundations, for which it is necessary both to provide models of the fundamentals of explainability
as well as to discuss the advantages and disadvantages of different proposals. The need for foundations is also linked to
the permanent challenge that the notion of explainability represents in Philosophy of Science. The paper aims to elaborate a
general theoretical framework to discuss foundational characteristics of explaining, as well as how solutions (events) would be
justified (explained). The approach, epistemological in nature, is based on the phenomenological-based approach to complex
systems reconstruction (which encompasses complex AI-based systems). The formalized perspective is close to ideas from
argumentation and induction (as learning). The soundness and limitations of the approach are addressed from Knowledge
representation and reasoning paradigm and, in particular, from Computational Logic point of view. With regard to the latter,
the proposal is intertwined with several related notions of explanation coming from the Philosophy of Science. | es |
dc.description.sponsorship | Agencia Estatal de Investigación PID2019-109152GB-I00/AEI/10.13039/501100011033 | es |
dc.format | application/pdf | es |
dc.format.extent | 23 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Complex and Intelligent Systems, 8 (2), 1579-1601. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Complex systems | es |
dc.subject | Explainable artificial intelligence | es |
dc.subject | Epistemological modeling | es |
dc.subject | Formal Concept Analysis | es |
dc.title | Knowledge representation for explainable artificial intelligence: modeling foundations from complex systems | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | PID2019-109152GB-I00/AEI/10.13039/501100011033 | es |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s40747-021-00613-5 | es |
dc.identifier.doi | 10.1007/s40747-021-00613-5 | es |
dc.contributor.group | Universidad de Sevilla. TIC-137: Lógica, Computación e Ingeniería del Conocimiento | es |
dc.journaltitle | Complex and Intelligent Systems | es |
dc.publication.volumen | 8 | es |
dc.publication.issue | 2 | es |
dc.publication.initialPage | 1579 | es |
dc.publication.endPage | 1601 | es |
dc.contributor.funder | Agencia Estatal de Investigación. España | es |