Show simple item record

Oportunidades y desafíos de la incorporación de algoritmos predictivos en el sistema de inteligencia estratégica de las Fuerzas Militares de Colombia

dc.contributor.authorSánchez Castro, Flor María
dc.contributor.authorGuevara Arismendy, Francisco Javier
dc.coverage.spatialBogotá D.C., Escuela Superior de Guerra “General Rafael Reyes Prieto”, 2025
dc.date.accessioned2026-05-14T02:17:30Z
dc.date.available2026-05-14T02:17:30Z
dc.date.issued2025
dc.date.submitted2025
dc.identifier.urihttps://hdl.handle.net/20.500.14205/12205
dc.description.abstractEl presente capítulo, examina las oportunidades y desafíos de incorporar los algoritmos predictivos en los sistemas de inteligencia estratégica militar, identificando la interacción e impacto en la toma de decisiones. A través del análisis bibliométrico, con un enfoque cualitativo y un alcance descriptivo de modelos de inteligencia artificial en el área de algoritmos predictivos, se argumenta cómo apoyan el proceso de toma de decisiones, a través del procesamiento de altos volúmenes de datos provenientes de múltiples fuentes. Adicionalmente, se identifican las oportunidades relevantes en términos de una automatización de análisis complejos, presentando desafíos tales como la explicabilidad, la calidad de los datos, la fiabilidad de las decisiones que se toman de manera autónoma y las implicaciones legales de su implementación. Este análisis contribuye al fortalecimiento de las capacidades prospectivas y anticipativas de la inteligencia estratégica militar, proporcionando insumos técnicos y conceptuales para la toma de decisiones basada en evidencia.es_ES
dc.description.sponsorshipEscuela Superior de Guerra “General Rafael Reyes Prieto”es_ES
dc.format.extent38 Páginas
dc.format.mimetypeapplication/pdfes_ES
dc.language.isospaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleOportunidades y desafíos de la incorporación de algoritmos predictivos en el sistema de inteligencia estratégica de las Fuerzas Militares de Colombiaes_ES
dcterms.bibliographicCitationAlcántara-Suárez, E. J. (2023). Análisis de la aplicación de machine learning en sistemas de defensa [Universidad Abierta de Cataluña]. https://tinyurl.com/nvjc377ves_ES
dcterms.bibliographicCitationAlfatemi, A., Rahouti, M., Amin, R., AlJamal, S., Xiong, K., & Xin, Y. (2024). Advancing DDoS attack detection: A synergistic approach using deep residual neural networks and synthetic oversampling. arXiv. https://doi.org/10.48550/arXiv.2401.03116es_ES
dcterms.bibliographicCitationAllen, G. C. (2017, 21 de diciembre). Project Maven brings AI to the fight against ISIS. https://tinyurl.com/mu8td5w3es_ES
dcterms.bibliographicCitationArdila-Castro, C. A., & Jiménez-Reina, J. (2020). Aportes teóricos a la construcción del concepto de inteligencia estratégica. Planeta. https://tinyurl.com/2ckc5eapes_ES
dcterms.bibliographicCitationArranz, R., Carramiñana, D., de Miguel, G., Besada, J. A., & Bernardos, A. M. (2025). Application of deep reinforcement learning to UAV swarming for ground surveillance. arXiv. https://doi.org/10.48550/arXiv.2501.08655es_ES
dcterms.bibliographicCitationAutio, E., Nambisan, S., Thomas, L. D. W., & Wright, M. (2020). Digital ecosystems and their implications for competitive strategy. Journal of Organization Design, 9(1), 12. https://doi.org/10.1186/s41469-020-00073-0es_ES
dcterms.bibliographicCitationAyub, M. Y., Mehdi, M. A., Tawaseem, S. G., Zukhraf, S. Z. N., & Zupash. (2022). Role of computational intelligence in cybersecurity. En M. Ouaissa, Z. Boulouard, M. Ouaissa, I. U. Khan, & M. Kaosar (Eds.), Big data analytics and computational intelligence for cybersecurity (pp. 125-144). Springer. https://doi.org/10.1007/978-3-031-05752-6_8es_ES
dcterms.bibliographicCitationBaboș, A., Iacob, C.-G., & Ene, C. (2022). Use of forecasting systems in the military decision-making process. Land Forces Academy Review, 27(4), 316–322. https://doi.org/10.2478/raft-2022-0040es_ES
dcterms.bibliographicCitationBarbosa Fontecha, J. L. (2021). Modelos predictivos para la rotación del talento humano. Tecnología, Investigación y Academia, 8(1), 54—71. https://tinyurl.com/5bpeexyres_ES
dcterms.bibliographicCitationBastos Martínez, L. (2019). Doctrina del Ejército Nacional: Componente de capacidad clave para afrontar los desafíos y amenazas de la nación en el siglo XXI. Experticia Militar, (7), 22–29. https://tinyurl.com/yvrd3bjses_ES
dcterms.bibliographicCitationBatra, S., Huang, Z., Petrenko, A., Kumar, T., Molchanov, A., & Sukhatme, G. S. (2022). Decentralized control of quadrotor swarms with end-to-end deep reinforcement learning. En Proceedings of the 5th Conference on Robot Learning (Vol. 164, pp. 576-586). Proceedings of Machine Learning Research. https://tinyurl.com/yr29k5z6es_ES
dcterms.bibliographicCitationBecerra‑Suárez, F. L., Fernández‑Román, I., & Forero, M. G. (2024). Improvement of Distributed Denial of Service attack detection through machine learning and data processing. Mathematics, 12(9), 1294. https://doi.org/10.3390/math12091294es_ES
dcterms.bibliographicCitationBello, A. M., Iorliam, A., & Asilkan, O. (2024, 30 de octubre). Data science insights and the classification of terrorist attacks in Nigeria using machine learning techniques. Global Journal of Computer Sciences: Theory and Research, 14(2).es_ES
dcterms.bibliographicCitationBertalanffy, L. von. (1968). General system theory: Foundations, development, applications. George Braziller.es_ES
dcterms.bibliographicCitationBudeanu, N. A. (2023). Bibliometric analysis regarding knowledge strategies in intelligence structures. Proceedings of the International Conference on Business Excellence, 17(1), 1179–1192. https://doi.org/10.2478/picbe-2023-0106es_ES
dcterms.bibliographicCitationCamacho, A., Gómez, J., & Galindo, C. (2024). Los desafíos éticos del uso de IA en la toma de decisiones [Trabajo de especialización, EAN]. Repositorio Insitucional https://tinyurl.com/4yphzctdes_ES
dcterms.bibliographicCitationCancelado, H. (2019). Doctrina Damasco: La interacción de la vida nacional y el dominio terrestre. Experticia Militar, (7), 76–78. https://tinyurl.com/yvrd3bjses_ES
dcterms.bibliographicCitationCONPES. (2020). Política Nacional para la Transformación Digital e Inteligente del Sector Defensa y Seguridad. Departamento Nacional de Planeación. https://tinyurl.com/mpdt2d28es_ES
dcterms.bibliographicCitationCortés González, D. C. (2019). Transformación de la inteligencia estratégica en Colombia: Hitos y retos en el escenario actual [Tesis de maestría, Universidad Nacional de Colombia]. Repositorio UNAL. https://tinyurl.com/nhja6rdpes_ES
dcterms.bibliographicCitationCreswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.es_ES
dcterms.bibliographicCitationDanish, M. (2024, 15 de julio). Enhancing cyber security through predictive analytics: Real-time threat detection and response. arXiv. https://doi.org/10.48550/arXiv.2407.10864es_ES
dcterms.bibliographicCitationDavenport, T. (2014). Big data at work: Dispelling the myths, uncovering the opportunities. Harvard Business Review. https://tinyurl.com/bdzmebeyes_ES
dcterms.bibliographicCitationGalán, J. J., Carrasco, R. A., & LaTorre, A. (2024). Military applications of machine learning: A bibliometric perspective. arXiv. https://doi.org/10.48550/arXiv.2410.17272es_ES
dcterms.bibliographicCitationGhasemaghaei, M., & Calic, G. (2019). Can big data improve firm decision quality? The role of data quality and data diagnosticity. Decision Support Systems, (120), 38–49. https://doi.org/10.1016/j.dss.2019.03.008es_ES
dcterms.bibliographicCitationGnodle, M. A., & Verran, D. (2021). Data-Enabled Decision-Making. U.S. Army. https://tinyurl.com/4ekdjtffes_ES
dcterms.bibliographicCitationGoodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. https://www.deeplearningbook.org/es_ES
dcterms.bibliographicCitationGunning, D., & Aha, D. W. (2019). DARPA’s explainable artificial intelligence (XAI) program. AI Magazine, 40(2), 44–58. https://doi.org/10.1609/aimag.v40i2.2850es_ES
dcterms.bibliographicCitationHabeeb, M. S. (2024). Predictive analytics and cybersecurity. En Intelligent Techniques for Predictive Data Analytics (pp. 151–169). Wiley https://doi.org/10.1002/9781394227990.ch8es_ES
dcterms.bibliographicCitationHan, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques (3a ed.). Morgan Kaufmann. https://tinyurl.com/579aeajzes_ES
dcterms.bibliographicCitationHe, H. Y., Zhu, W. X., Li, R. Y., & Deng, Q. Y. (2020). An executable modeling and analyzing approach to C4ISR architecture. Journal of Systems Engineering and Electronics, 31(1), 109–117. https://doi.org/10.21629/JSEE.2020.01.12es_ES
dcterms.bibliographicCitationHeuer, R. J. (1999). Psychology of intelligence analysis. Center for the Study of Intelligence.es_ES
dcterms.bibliographicCitationHilton-Shomron, Y. D. (2024, febrero 23). Report: Revolutionizing Military Strategy: Integrating AI for Predictive Analytics and Real-Time Battle Planning. LinkedIn. https://www.linkedin.com/pulse/report-revolutionizing-military-strategy-integratinghilton-shomron-dy9rees_ES
dcterms.bibliographicCitationImran, I.I. (2025). Exploiting anomalies with data mining techniques to enhance cloud security. Mathematical Modelling of Engineering Problems, 12(2), 636646. https://doi.org/10.18280/mmep.120227es_ES
dcterms.bibliographicCitationJaramillo, J. (2024). El marco jurídico para la regulación de la inteligencia artificial en Colombia: Retos y Perspectivas en la Creación de un Régimen Normativo [Universidad Cooperativa de Colombia]. https://repository.ucc.edu.co/server/api/core/bitstreams/1f7766ea-aa98-4e91-b391-59ac4bdbc32b/contentes_ES
dcterms.bibliographicCitationJoint Chiefs of Staff. (2022). Joint Intelligence (JP 2-0). U.S. Department of Defense. https://tinyurl.com/mw8fchd7es_ES
dcterms.bibliographicCitationKelleher, J. D., Mac Namee, B., & D’Arcy, A. (s. f.). Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies. MIT Press. https://tinyurl.com/yfhfz3zdes_ES
dcterms.bibliographicCitationKhan, A. A., Badshah, S., Liang, P., Waseem, M., Khan, B., Ahmad, A., Fahmideh, M., Niazi, M., & Akbar, M. A. (2021). Ethics of AI: A systematic literature review of principles and challenges. arXiv. https://doi.org/10.48550/arXiv.2109.07906es_ES
dcterms.bibliographicCitationKiss, J., Skraba, F., & De Oliveira, C. (2023). The future of intelligence: AI, big data and challenges for policymakers. Journal of Defense Studies, 10(3), 47–60.es_ES
dcterms.bibliographicCitationLandauer, M., Skopik, F., Stojanović, B., Flatscher, A., & Ullrich, T. (2025). A review of time-series analysis for cybersecurity analytics: From intrusion detection to attack prediction. International Journal of Information Security, 24(3). https://doi.org/10.1007/s10207-024-00921-0es_ES
dcterms.bibliographicCitationLappin, Y. (2023). Embracing big data and AI strategically: The digital transformation of the IDF. En Leveraging Innovation and Artificial Intelligence (Capítulo 7). The Air Power Journal, Third Edition. Begin-Sadat Center for Strategic Studies. https://theairpowerjournal.com/big-data-ai-digital-transformation-idf/es_ES
dcterms.bibliographicCitationLiwång, H., Kent E, A., Bang, M., & Tärnholm, T. (2023). How can systemic perspectives on defence capability development be strengthened? Defence Studies, 23(3), 399–420. https://doi.org/10.1080/14702436.2023.2239722es_ES
dcterms.bibliographicCitationMárquez-Díaz, J. E. (2024). Benefits and challenges of military artificial intelligence in the field of defense. Computación y Sistemas, 28(2), 309–323. https://doi.org/10.13053/cys-28-2-4684es_ES
dcterms.bibliographicCitationMarr, B. (2016). Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. Wiley.es_ES
dcterms.bibliographicCitationMcDowell, K., Novoseller, E., Madison, A., Goecks, V. G., & Kelshaw, C. (2024). Re-Envisioning Command and Control. arXiv. https://doi.org/10.48550/arXiv.2402.07946es_ES
dcterms.bibliographicCitationMeerveld, H., & Lindelauf, R. (2024). Data science in military decision‑making: Foci and gaps. Global Society, 39(2), 103–129. https://doi.org/10.1080/13600826.2024.2353657es_ES
dcterms.bibliographicCitationMinisterio de Defensa Nacional [Mindefensa]. (2024). Plan Estratégico del Sector Defensa y Seguridad: Guía de planeamiento estratégico del sector defensa 2022-2026. Mindefensa. https://tinyurl.com/2em77pp7es_ES
dcterms.bibliographicCitationMinisterio de Defensa Nacional [Mindefensa]. (2024). Plan Nacional de Transformación Digital del Sector Defensa 2023–2030. Mindefensa. https://tinyurl.com/55kcbddhes_ES
dcterms.bibliographicCitationMinistry of Defence (UK). (2022). Defence Artificial Intelligence Strategy. Ministry of Defence. https://tinyurl.com/2s486shdes_ES
dcterms.bibliographicCitationMonzón-Baeza, V., Parada, R., Concha Salor, L., & Monzó, C. (2025). AI-driven tactical communications and networking for defense: A survey and emerging trends. arXiv. https://doi.org/10.48550/arXiv.2504.05071es_ES
dcterms.bibliographicCitationNATO. (2016). AJP-2: Allied Joint Doctrine for Intelligence, Counter-Intelligence and Security (Edition A, Version 2). North Atlantic Treaty Organization. https://jadl.act.nato.int/ILIAS/data/testclient/lm_data/lm_152845/Linear/JISR04222102/sharedFiles/AJP2.pdfes_ES
dcterms.bibliographicCitationNeira, A., Kantarci, B., & Nogueira, M. (2023). Distributed denial of service attack prediction: Challenges, open issues and opportunities. Computer Networks, 222(3), 109553. https://doi.org/10.1016/j.comnet.2022.109553es_ES
dcterms.bibliographicCitationNUVU. (2024). Inteligencia Artificial: Revolucionando el sector de la defensa en Colombia. NUVU. https://tinyurl.com/547kv3kres_ES
dcterms.bibliographicCitationPellerin, C. (2017, 21 de julio). Project Maven to deploy computer algorithms to war zone by year’s end. DoD News, Defense Media Activity. https://tinyurl.com/evys32y2es_ES
dcterms.bibliographicCitationPherson, R., & Pherson, K. (2021). Critical Thinking for Strategic Intelligence (3rd ed.). CQ Press.es_ES
dcterms.bibliographicCitationPhythian, M. (2021). Conclusion: The development of critical intelligence studies. Intelligence and National Security, 36(4), 615–620. https://doi.org/10.1080/02684527.2021.1912266es_ES
dcterms.bibliographicCitationPili, G. (2019). Intelligence and social epistemology: Toward a social epistemological theory of intelligence. Social Epistemology, 33(6), 574–592. https://doi.org/10.1080/02691728.2019.1658823es_ES
dcterms.bibliographicCitationPreece, A., Braines, D., Cerutti, F., & Pham, T. (2019). Explainable AI for Intelligence Augmentation in Multi-Domain Operations. arXiv. https://doi.org/10.48550/arXiv.1910.07563es_ES
dcterms.bibliographicCitationProbasco, E., Toner, H., Burtell, M., & Rudner, T. G. J. (2025, abril). AI for military decision-making. CSET. https://cset.georgetown.edu/wp-content/uploads/CSET-AI-for-Military-Decision-Making.pdfes_ES
dcterms.bibliographicCitationProvost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O’Reilly Media.es_ES
dcterms.bibliographicCitationQuiñones-Sigala, J. (2023). Aplicaciones de la inteligencia artificial en contribución a la defensa nacional de Chile: Una oportunidad para la integración de la defensa, la industria y la academia. Revista Política y Estrategia, (141), 155–185. https://doi.org/10.26797/rpye.vi141.1044es_ES
dcterms.bibliographicCitationRashid, J., Batool, A., Kim, J., Wasif Nisar, M., Hussain, A., Juneja, S., & Kushwaha, P. (2022). An augmented artificial intelligence approach for chronic diseases prediction. Frontiers in Public Health, 10, 860396. https://doi.org/10.3389/fpubh.2022.860396es_ES
dcterms.bibliographicCitationRizve, M. N., Duarte, K., Rawat, Y. S., & Shah, M. (2021). In defense of pseudo-labeling: An uncertainty-aware pseudo-label selection framework for semi‑supervised learning. arXiv. https://doi.org/10.48550/arXiv.2101.06329es_ES
dcterms.bibliographicCitationRussell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4a ed.). Pearson.es_ES
dcterms.bibliographicCitationSánchez, J. L. (2025, 4 de febrero). Inteligencia artificial en apoyo a la inteligencia militar. IEEE - Ministerio de Defensa de España. https://tinyurl.com/3j7yu9wbes_ES
dcterms.bibliographicCitationSarker, I. H., Janicke, H., Maglaras, L., & Camtepe, S. (2023). Data-driven intelligence can revolutionize today’s cybersecurity world: A position paper. arXiv. https://doi.org/10.48550/arXiv.2308.05126es_ES
dcterms.bibliographicCitationScharre, P., & Horowitz, M. C. (2019). A stable nuclear future? The impact of autonomous systems and artificial intelligence (ARYA Working Paper No. 1912.05291). arXiv. https://doi.org/10.48550/arXiv.1912.05291es_ES
dcterms.bibliographicCitationShapira, I. (2020a). The limited influence of competitive intelligence over corporate strategy in Israel: Historical, organizational, conceptual, and cultural explanations. Intelligence and National Security, 36(1), 95-115. https://doi.org/10.1080/02684527.2020.1796338es_ES
dcterms.bibliographicCitationShapira, I. (2020b). The main challenges facing strategic intelligence. Strategic Assessment, 23(1), 4–22. https://www.inss.org.il/wp-content/uploads/2022/12/Adkan23.1Eng_4.pdfes_ES
dcterms.bibliographicCitationSharma, D., & Phulli, K. (2020). Forecasting and analyzing the military expenditure of India using Box‑Jenkins ARIMA model. arXiv. https://doi.org/10.48550/arXiv.2011.06060es_ES
dcterms.bibliographicCitationShu, R., Xia, T., Tu, H., Williams, L., & Menzies, T. (2022). Reducing the cost of training security classifier via optimized semi-supervised learning. arXiv. https://doi.org/10.48550/arXiv.2205.00665es_ES
dcterms.bibliographicCitationSurma, J. (2024). Deep learning in military applications: Threats and opportunities. Safety & Defense, 10(1), 1–7. https://doi.org/10.37105/sd.214es_ES
dcterms.bibliographicCitationTaddeo, M., McNeish, D., Blanchard, A., & Edgar, E. (2021). Ethical principles for artificial intelligence in national defence. Philosophy & Technology, 34, 1707–1729. https://doi.org/10.1007/s13347-021-00482-3es_ES
dcterms.bibliographicCitationVan Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3es_ES
dcterms.bibliographicCitationVillamin, P., Lopez, V., Thapa, D. K., & Cleary, M. (2024). A worked example of qualitative descriptive design: A step‑by‑step guide for novice and early career researchers. Journal of Advanced Nursing, 81(8), 5181–5195. https://doi.org/10.1111/jan.16481es_ES
dcterms.bibliographicCitationWilliams, B., & Qian, L. (2025). Semi‑supervised learning for intrusion detection in large computer networks. Applied Sciences, 15(11), 5930. https://doi.org/10.3390/app15115930es_ES
dcterms.bibliographicCitationWilner, A., & Atkinson, R. (2025, March 17). Artificial intelligence and national defence: A strategic foresight analysis (CIGI Paper No. 316). Centre for International Governance Innovation. https://www.cigionline.org/publications/artificial-intelligence-and-national-defence-a-strategic-foresight-analysis/es_ES
dcterms.bibliographicCitationYue, L., Yang, R., Zuo, J., & Zhang, Y. (2023). Research on reinforcement learning-based safe decision-making methodology for multiple unmanned aerial vehicles. Frontiers in Neurorobotics, 16, 1105480. https://doi.org/10.3389/fnbot.2022.1105480es_ES
dcterms.bibliographicCitationZambrano González, E. E. (2025). Ética de la inteligencia artificial militar: análisis de principios, marcos normativos y desafíos futuros. Revista Ciberespacio, Tecnología e Innovación, 4(7), 43–60. https://doi.org/10.25062/2955-0270.4943es_ES
dcterms.bibliographicCitationZhu, J., Kuang, M., Zhou, W., Shi, H., & Han, X. (2023). Mastering air combat game with deep reinforcement learning. Defence Technology, (34), 295—312. https://doi.org/10.1016/j.dt.2023.08.019es_ES
datacite.rightshttp://purl.org/coar/access_right/c_16eces_ES
oaire.resourcetypehttp://purl.org/coar/resource_type/c_3248es_ES
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaes_ES
dc.audiencePúblico generales_ES
dc.identifier.instnameEscuela Superior de Guerra "General Rafael Reyes Prieto"es_ES
dc.identifier.reponameRepositorio ESDEGes_ES
dc.publisher.placeBogotáes_ES
dc.publisher.programCurso de Información Militar (CIM)es_ES
dc.relation.citationEdition38 Páginases_ES
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.subject.keywordsAlgoritmos Predictivoses_ES
dc.subject.keywordsInteligencia Artificiales_ES
dc.subject.keywordsInteligencia Estratégicaes_ES
dc.subject.keywordsProspectiva Operativaes_ES
dc.subject.keywordsSistemases_ES
dc.type.driverinfo:eu-repo/semantics/bookPartes_ES
dc.type.hasversioninfo:eu-repo/semantics/restrictedAccesses_ES
dc.type.spaCapítulo de Libroes_ES


Files in this item

Thumbnail
Name:
Capítulo 6- Inteligencia ...
Size:
3.552Mb
Format:
PDF
View/Open
Thumbnail
Name:
license_rdf
Size:
805bytes
Format:
application/rdf+xml
View/Open

This item appears in the following Collection(s)

Show simple item record

http://creativecommons.org/licenses/by-nc-nd/4.0/
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/