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    dc.contributor.authorCazares Alegría, Hipatia.-
    dc.contributor.authorPico Valencia, Pablo.-
    dc.date.accessioned2025-04-21T22:24:07Z-
    dc.date.available2025-04-21T22:24:07Z-
    dc.date.issued2025-01-01-
    dc.identifier.citationCazares Alegría , H., & Pico Valencia, P. (2025). Agentes de software basados en técnicas de aprendizaje automático. Perspectivas desde 2010 hasta 2023. REVISTA COLOMBIANA DE TECNOLOGIAS DE AVANZADA (RCTA), 1(45), 39–56. https://doi.org/10.24054/rcta.v1i45.3131es_CO
    dc.identifier.issn1692-7257-
    dc.identifier.issn2500-8625-
    dc.identifier.urihttp://repositoriodspace.unipamplona.edu.co/jspui/handle/20.500.12744/9425-
    dc.descriptionEste estudio tiene como objetivo analizar las principales propuestas teóricas y prácticas en las que se han integrado agentes de software con modelos de aprendizaje automático para determinar su alcance en términos de inteligencia, proactividad, colaboración y aprendizaje. Para el desarrollo de esta investigación se usó la metodología propuesta por Kofod-Peterson. Se analizaron 55 estudios los cuales mostraron que, en la interacción entre agentes de software y aprendizaje automático, los procesos cooperativos y colaborativos se han utilizado ampliamente en la resolución de problemas de control y en la optimización de datos en escenarios distribuidos como el hogar, juegos y las telecomunicaciones. También se evidenció que se utilizaron principalmente modelos de aprendizaje por refuerzo en comparación con los modelos de aprendizaje automático porque contribuyen de manera más significativa al modelado cooperativo de tareas en sistemas inteligentes.es_CO
    dc.description.abstractThis study aims to analyze the main theoretical and practical proposals in which software agents have been integrated with machine learning models to determine their scope in terms of intelligence, proactivity, collaboration and learning. For the development of this research, the methodology proposed by Kofod-Peterson was carried out. Applying the methodology, 55 studies were analyzed. The studies showed that in the interaction between software agents and machine learning, cooperative and collaborative processes have been widely used in the resolution of control problems and in the optimization of data in distributed scenarios such as home, games and telecommunication. It was also found that mostly reinforcement learning models were used compared to machine learning models because they contribute more significantly to cooperative task modeling, which is widely used in intelligent systems.es_CO
    dc.format.extent18es_CO
    dc.format.mimetypeapplication/pdfes_CO
    dc.language.isoeses_CO
    dc.publisherAldo Pardo García, Revista Colombiana de Tecnologías de Avanzada, Universidad de Pamplona.es_CO
    dc.relation.ispartofseries39;56-
    dc.subjectaprendizaje automáticoes_CO
    dc.subjectagente softwarees_CO
    dc.subjectsistema multiagentees_CO
    dc.subjectinteligencia artificiales_CO
    dc.titleAgentes de software basados en técnicas de aprendizaje automático. Perspectivas desde 2010 hasta 2023es_CO
    dc.typehttp://purl.org/coar/resource_type/c_2df8fbb1es_CO
    dc.date.accepted2024-12-15-
    dc.description.editionVol. 1 Núm. 45 (2025): Enero – Junioes_CO
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