Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning

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Fecha de publicación:
2026
Institución:
Universidad de Caldas
Repositorio:
Repositorio Institucional U. Caldas
Idioma:
spa
OAI Identifier:
oai:repositorio.ucaldas.edu.co:ucaldas/26715
Acceso en línea:
https://repositorio.ucaldas.edu.co/handle/ucaldas/26715
Palabra clave:
620 - Ingeniería y operaciones afines
2. Ingeniería y Tecnología
AI Planning
Capital Intelectual
Planificación en Inteligencia Artificial
Planificación Automática
Innovación Abierta
Extensión Universitaria
Ingeniería
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id REPOUCALDA_9feb5dad9473d65b2c99c8ba674276ab
oai_identifier_str oai:repositorio.ucaldas.edu.co:ucaldas/26715
network_acronym_str REPOUCALDA
network_name_str Repositorio Institucional U. Caldas
repository_id_str
dc.title.none.fl_str_mv Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
Design of a model for open innovation and intellectual capital management in the extension mission of public higher education institutions in Colombia, supported by artificial intelligence planning
title Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
spellingShingle Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
620 - Ingeniería y operaciones afines
2. Ingeniería y Tecnología
AI Planning
Capital Intelectual
Planificación en Inteligencia Artificial
Planificación Automática
Innovación Abierta
Extensión Universitaria
Ingeniería
title_short Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
title_full Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
title_fullStr Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
title_full_unstemmed Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
title_sort Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI Planning
dc.contributor.none.fl_str_mv Castillo Ossa, Luis Fernando
Duque Méndez, Néstor Darío
Inteligencia Artificial
Garrido Tejero, Antonio
Carrillo, Eduardo
dc.subject.none.fl_str_mv 620 - Ingeniería y operaciones afines
2. Ingeniería y Tecnología
AI Planning
Capital Intelectual
Planificación en Inteligencia Artificial
Planificación Automática
Innovación Abierta
Extensión Universitaria
Ingeniería
topic 620 - Ingeniería y operaciones afines
2. Ingeniería y Tecnología
AI Planning
Capital Intelectual
Planificación en Inteligencia Artificial
Planificación Automática
Innovación Abierta
Extensión Universitaria
Ingeniería
description Figuras, tablas
publishDate 2026
dc.date.none.fl_str_mv 2026-03-19T15:10:20Z
2026-03-19T15:10:20Z
2026-03-17
dc.type.none.fl_str_mv Trabajo de grado - Doctorado
http://purl.org/coar/resource_type/c_db06
Text
info:eu-repo/semantics/doctoralThesis
dc.identifier.none.fl_str_mv https://repositorio.ucaldas.edu.co/handle/ucaldas/26715
Universidad de Caldas
Repositorio Institucional Universidad de Caldas
repositorio.ucaldas.edu.co
url https://repositorio.ucaldas.edu.co/handle/ucaldas/26715
identifier_str_mv Universidad de Caldas
Repositorio Institucional Universidad de Caldas
repositorio.ucaldas.edu.co
dc.language.none.fl_str_mv spa
language spa
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dc.format.none.fl_str_mv 308 páginas
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dc.publisher.none.fl_str_mv Universidad de Caldas
Facultad de Inteligencia Artificial e Ingenierías
Colombia, Caldas, Manizales
Doctorado en Ingeniería
publisher.none.fl_str_mv Universidad de Caldas
Facultad de Inteligencia Artificial e Ingenierías
Colombia, Caldas, Manizales
Doctorado en Ingeniería
institution Universidad de Caldas
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Diseño de un modelo para la innovación abierta y la gestión del capital intelectual en la misión de extensión de las instituciones de educación superior públicas de Colombia soportado en AI PlanningDesign of a model for open innovation and intellectual capital management in the extension mission of public higher education institutions in Colombia, supported by artificial intelligence planning620 - Ingeniería y operaciones afines2. Ingeniería y TecnologíaAI PlanningCapital IntelectualPlanificación en Inteligencia ArtificialPlanificación AutomáticaInnovación AbiertaExtensión UniversitariaIngenieríaFiguras, tablasThis doctoral dissertation focused on defining the integration of open innovation and intellectual capital, grounded in Resource-Based Theory, and applied to public university extension in Colombia, so that an artificial-intelligence planning environment could automate the generation of plans for the open-innovation and intellectual-capital processes required to execute extension projects. Recent research indicates that public higher education institutions have not fully defined their role in open-innovation processes and in managing intellectual capital beyond traditional models such as the triple, quadruple, and quintuple helix. These approaches position universities as knowledge generators, yet they do not ensure the systematic transfer of that knowledge to society through university extension. In addition, a substantial portion of the scientific literature highlights major challenges arising from the democratized use of artificial intelligence, which affects the installed capabilities of university extension in light of new social and technological realities. Process models are often designed manually as declarative flow diagrams by experts with deep knowledge of organizational activities. In public university extension, this leads to a large set of activity rules that becomes difficult to maintain due to limited flexibility, scale, and complexity. Therefore, it is necessary to automatically discover the processes required to address social dynamics under uncertainty through university extension, supported by open innovation and intellectual capital. This dissertation incorporates three components. The first integrates intellectual capital with the outbound open-innovation model within the Resource-Based Theory framework to produce a conceptual model that treats intellectual capital as the internal capabilities of public university extension and outbound open innovation as its external capability flows. This approach is developed through a cross-impact matrix and validated in university-extension case studies. The second component addresses process automation through the construction of BPMN 2.0 flow diagrams for education projects, as well as projects involving technological development and consultancy. This provides the baseline knowledge for an artificial-intelligence planning environment based on Hierarchical Task Network (HTN) planning. In this approach, a parsing algorithm translates the BPMN structure into operators, actions, and methods for building the action model (domain). It also enables the construction of planning problems by capturing extension-project information as BPMN flow diagrams. Generating BPMN diagrams is a precondition for building the domain and defining specific HTN planning problems. The third component focuses on plan generation assisted by a pre-planning algorithm using the SHOP2, PyHOP, and GTPyhop planners for implementing or executing the projects described in the BPMN diagrams. Plan generation is supported by HTN planning languages such as PDDL-HTN or HDDL (Hierarchical Domain Definition Language). The experimental results are validated through case studies and consolidated in a platform that integrates these approaches, named PlanProjU (Planning + Project + University). AI Planning addresses the study and computational modeling of capabilities characteristic of human intelligence, especially those related to goal setting, action selection, and decision-making under constraints and changing environments. From the perspective of Artificial Cognitive Systems, this approach seeks to explicitly represent the deliberative reasoning that guides goal-oriented behavior, using symbolic and hierarchical models such as classical planning and HTN planning. These models allow for the decomposition of complex tasks into manageable subtasks and the construction of coherent action sequences. Within this framework, planning is understood as a central mechanism of cognition, as it integrates knowledge, inference, and evaluation of alternatives to anticipate outcomes, optimize resource utilization, and adapt behavior. This makes it a key field for designing artificial systems with cognitive capabilities closer to those of humans. The main contributions of this dissertation can be summarized as follows: (i) the definition of an integrated intellectual-capital and open-innovation model, grounded in Resource-Based Theory and applied so far, for the first time—to university extension, as an alternative to related work that validates conceptual integrations but does not adopt them as an extension-oriented reference framework; and (ii) the proposal of a university-extension model, framed by open innovation and intellectual capital, supported by a hierarchical AI planning environment, together with the construction of that planning environment to automate plans for extension projects. Validation tests were conducted in extension scenarios at Universidad Nacional de Colombia (Manizales campus), Universidad de Caldas, and Universidad Tecnológica de Pereira (UTP). The results showed the need to prepare extension staff to use the BPMN format. For this purpose, PlanProjU includes a BPMN usage guide, and extension experts were encouraged to use the BPMN-GPT tool, which facilitates converting extension PDF documents into BPMN diagrams. The projects followed different formats. In the case of Universidad de Caldas, projects included both formulation-stage documents and final reports from executed projects. In the cases of Universidad Nacional de Colombia (Manizales campus) and Universidad Tecnológica de Pereira, the institutions shared executed projects in formulation documents. In total, 36 tests were performed on the PlanProjU platform using these projects. After reviewing the planning domain and problem, the extension user can approve or reject the generated plans. At the end of the validation stage, PlanProjU executed without issues. Moreover, in the instrument administered to extension staff, respondents stated that the platform is user-friendly and produces plans that can be implemented within the organization. Finally, based on the concepts and the proposed model, an experimental web platform for open innovation and intellectual capital in university extension was designed and implemented. Its main function is to enable project formulators to upload a BPMN diagram of their project in advance and automatically generate the planning domain, while allowing the definition of planning problems so that SHOP2, PyHOP, and GTPyhop can produce plans for project execution or implementation automatically. The system was designed for extension projects in public universities in Colombia under a client–server architecture, using free and cross-platform tools so that it can be accessed by interested individuals or institutions.La presente tesis de doctorado se centró en definir la integración de la innovación abierta y el capital intelectual basado en la teoría del recurso aplicado a la extensión universitaria publica de Colombia, de tal forma que bajo un ambiente de planificación en inteligencia artificial se automatizará la generación de los planes en los procesos de innovación abierta y capital intelectual necesarios para ejecutar los proyectos de extensión. Recientes investigaciones señalan que las instituciones de educación superior públicas no tienen completamente definido su papel en procesos de innovación abierta y la gestión de su capital intelectual, más allá de lo propuesto en modelos tradicionales como la triple, cuádruple hélice y quíntupla hélice, que la convierte en un actor generador de conocimiento, pero sin la capacidad de transferirlo de forma sistemática a la sociedad desde la extensión universitaria. De igual forma gran parte de la literatura científica manifiestan la existencia de grandes desafíos resultados del uso democratizado de la inteligencia artificial, las cuales afectan las capacidades instaladas de extensión universitaria frente a la nuevas realidades sociales y tecnológicas. Los modelos de procesos suelen ser diseñados como diagramas de flujo declarativos de forma manual por parte de un experto que posee un profundo conocimiento de las actividades realizadas en las organizaciones. Esto implica que, como en el caso de la extensión universitaria pública, existan una gran cantidad de reglas de actividades difíciles de mantener por su falta de flexibilidad, tamaño y complejidad. Por ello es necesario descubrir los procesos necesarios ante las dinámicas de incertidumbre sociales que requieren ser atendidas mediante la extensión universitaria de manera automática desde la innovación abierta y el capital intelectual. En esta tesis se han incorporado tres componentes. El primero consiste en integrar los modelos teóricos primero consiste capital intelectual con el modelo de innovación abierta de salida en el marco de la teoría del recurso en las organizaciones para obtener un modelo conceptual que considera al capital intelectual como las capacidades internas de la extensión universitaria publica y como capacidades externas el flujo de salida de innovación abierta. Este enfoque se desarrolla apoyado en matriz de impacto cruzado validado en casos de estudio de extensión universitaria. El segundo es la automatización de procesos mediante la construcción de diagramas de flujo de tipo BPMN 2.0 para los proyectos de educación, con creación y consultoría tecnológica, lo que permite obtener el conocimiento de base para un ambiente de planificación en inteligencia artificial del tipo Hierarchical Task Network Planning (HTN), este enfoque diseña un algoritmo de parseo que permite traducir la estructura del BPMN en operadores, acciones y métodos para la construcción del modelo de acciones o dominio, de igual forma se permite construir los problemas de planificación basado en la captura de la información de los proyectos de extensión en forma de diagramas de flujo en el formato BPMN. La generación de los diagramas de BPMN es una precondición para iniciar la construcción del dominio y poder definir problemas específicos para planificación HTN. El tercer componente consiste en la generación de planes asistido por algoritmo de preplanificación para el uso de los planificadores SHOP2, PYHOP y GTPyhop para la implementación o ejecución de los proyectos descritos en los diagramas BPMN. La generación de planes esta soportada en los lenguajes de planificación PDDL-HTN) o HDDL (Hierarchical Definition Domain Language). Los resultados experimentales se validan en casos de estudio que convergen en una plataforma que integra ambos enfoques denominada PlanProjU (Planificación + Proyecto + Universidad). AI Planning aborda el estudio y la modelación computacional de capacidades propias de la inteligencia humana, en especial aquellas relacionadas con la formulación de metas, la selección de acciones y la toma de decisiones bajo restricciones y entornos cambiantes. Desde la línea de Sistemas Cognitivos Artificiales, este enfoque busca representar de manera explícita el razonamiento deliberativo que guía la conducta orientada a objetivos, mediante modelos simbólicos y jerárquicos como la planificación clásica y la planificación HTN que permiten descomponer tareas complejas en subtareas manejables y construir secuencias de acciones coherentes. En este marco, la planificación se entiende como un mecanismo central de la cognición, ya que integra conocimiento, inferencia y evaluación de alternativas para anticipar resultados, mejorar el uso recursos y adaptar el comportamiento, lo cual la convierte en un campo clave para diseñar sistemas artificiales con capacidades cognitivas más cercanas a las humanas. Se puede resumir los aportes principales de esta tesis en la definición de un modelo integrado de capital intelectual e innovación abierta bajo el marco teórico de la teoría del recurso en las organizaciones aplicado por primera vez hasta el momento en la extensión universitaria alternativo a los trabajos relacionados que se enfocan en la integración en modelos conceptuales validados pero no usados como marco de referencia en extensión universitaria; en la propuesta de un modelo de extensión universitaria bajo el marco de innovación abierta y capital intelectual soportado en un ambiente de planificación en inteligencia artificial tipo jerárquica y la construcción del ambiente de planificación para la automatización de planes para proyectos de extensión. De igual forma las pruebas de validación se realizaron en escenarios de extensión de la Universidad Nacional de Colombia sede Manizales, Universidad de Caldas y Universidad Tecnológica de Pereira (UTP), en que evidencio la necesidad de preparar a los funcionarios de extensión en el uso del formato BPMN. Para esto se prepara en la plataforma PlanProjU una guía de uso de BPMN, se fomenta en los expertos de extensión usar la herramienta BPMN-GPT, que facilita la conversión de documentos en extensión pdf a diagramas BPMN. Entre las características de los proyectos se tiene diferentes formatos y en caso de la Universidad de Caldas, tiene proyectos de extensión en su fase de formulación e informes de proyectos ejecutados y en el caso de la Universidad Nacional de Colombia sede Manizales y la Universidad Tecnológica de Pereira, compartieron proyectos ejecutados, en documentos de formulación. En total se realizaron 36 pruebas en la plataforma PlanProjU, con los diferentes proyectos que se usaban, el usuario de extensión una vez revisado el problema y dominio de planificación tiene la capacidad de aprobar o rechazar la solución de planes. Al finalizar la etapa de validación de la plataforma PlanProjU, se observa que la misma ejecuta sin problema alguno, incluso en el instrumento aplicado a los funcionarios de extensión manifestaron, en su respuesta que la plataforma es amigable y genera planes que puede ser implementado en la organización. De igual forma, a partir de los conceptos y la propuesta del modelo planteado, se diseña y construye una plataforma web experimental de innovación abierta y capital intelectual para la extensión universitaria, cuya función principal es facilitar a los formuladores de proyectos cargar de forma previa un diagrama BPMN de su proyecto y generar de forma automática dominio y permitir la definición de problemas de planificación para que a través de uso de los planificadores SHOP2, PYHOP y GTPyhop se obtengan planes para la ejecución o implementación de los proyectos de forma automática. El sistema fue diseñado para proyectos de extensión en las universidades públicas de Colombia, en un esquema cliente/servidor, con herramientas libres y multiplataforma para que pueda ser accesible a las personas o instituciones interesadas.Contenido -- Capítulo -- Introducción -- Antecedentes de la investigación extensión universitaria, OI e IC -- Antecedentes de la investigación cambios en BPMN y diagramas de flujo -- Antecedentes de la investigación Business Process Automation -- Antecedentes AI planning -- Problema de investigación -- Preguntas emergentes de la investigación -- Hipótesis y objetivos de investigación -- Hipótesis -- Objetivo general -- Objetivos específicos -- Justificación -- Limitaciones -- Metodología -- Principales contribuciones -- Organización del documento -- Difusión de resultados -- Capítulo -- Conceptos generales y revisión sistemática de literatura -- Revisión sistemática de literatura -- Metodología para la revisión sistemática de literatura -- Definición de preguntas de investigación -- Proceso de búsqueda -- Criterios de selección -- Extracción de datos -- Resultados -- Discusión -- Vacío del conocimiento -- Naturaleza del capital intelectual (IC) -- Enfoques de IC -- Enfoques de medición para IC -- Especificación declarativa de procesos -- Lógica modal anulable -- Derivación lógica -- Derivación como planes -- Business Process Management Notation (BPMN) -- IC en las instituciones de educación superior (IES) -- Instituciones de educación superior públicas en Colombia -- Modelos de IC -- Naturaleza de la OI -- Inteligencia artificial, IC y OI -- Extensión universitaria -- Extensión en las IES públicas de Colombia -- Técnicas de AI planning -- Planificación heurística -- Planificación con landmark -- Planificación basada en grafos -- Planificación temporal -- Planificación de redes de tareas jerárquicas -- Conclusiones del capítulo -- Capítulo -- AI planning y el problema de satisfacción de restricciones (CSP) -- AI planning -- PDDL comparado con la formulación SAS+ -- Gráficos de transición de dominio -- Métodos de planificación -- Planificación basada en búsqueda heurística -- Satisfactibilidad basada en planificación -- Problema de satisfacción de restricciones (CSP) -- Problema de satisfacción de restricciones (CSP) -- Planificadores basados en restricciones -- Conclusiones del capítulo -- Capítulo -- Modelo de OI e IC -- Trabajos relacionados con procesos declarativos -- Integración de OI e IC -- Tipos de extensión universitaria bajo el marco de OI e IC -- Modelo conceptual de OI e IC tipo proceso -- Proceso de OI para la extensión universitaria pública de Colombia -- Proceso de IC para la extensión universitaria pública de Colombia -- Proceso de extensión universitaria pública de Colombia -- Proceso integrado de OI e IC para extensión universitaria pública -- Conclusiones del capítulo -- Capítulo -- Preliminares del modelo de AI planning para OI e IC en extensión universitaria pública de Colombia -- Trabajos relacionados de AI planning y procesos -- Herramientas de AI planning para el ambiente de planificación -- Preprocesamiento de reglas para el proceso de OI e IC -- Consideraciones sobre hierarchical task network planning (HTN) -- Definiciones de HTN -- SHOP2 -- Pyhop -- HDDL -- GTPyhop -- Conclusiones del capítulo -- Capítulo -- Modelo de AI planning para OI e IC en extensión universitaria pública en Colombia -- Ambiente de planificación diseñado: PlanProjU y planes resultantes -- Estructura del ambiente de planificación -- Algoritmo de parseo en el ambiente de planificación -- Problemas de planificación -- Planes y resultados -- Conclusiones del capítulo -- Capítulo -- Sistema PlanProjU y casos de estudio -- Plataforma experimental PlanProjU -- Arquitectura de PlanProjU -- Capas de PlanProjU -- Componentes de PlanProjU -- Capas de uso de la plataforma PlanProjU -- Fases operativas de la plataforma PlanProjU -- Modelo de datos de la plataforma PlanProjU -- Caso de estudio con PlanProjU -- Caso de estudio -- Caracterización de OI e IC en las universidades públicas de Colombia -- Pretest -- Resultados de validación de PlanProjU -- Conclusiones del capítulo -- Capítulo -- Conclusiones y trabajo futuro -- Conclusiones y aportes -- Trabajo futuro -- Anexo: Matriz de caracterización OI e IC para extensión universitaria pública en Colombia -- Anexo: Tabla de enfoque de investigación de IC y extensión universitaria -- Anexo: Cuestionario de intervención de OI e IC en extensión universitaria pública en Colombia -- Anexo: Requisitos mínimos de la plataforma -- Información general -- Propósito del documento -- Datos del proyecto -- Descripción general del sistema -- Funciones del producto -- Requisitos funcionales -- Gestión de usuarios -- Registro de usuarios -- Autenticación -- Gestión de roles -- Procesamiento de proyectos -- Carga de archivos BPMN -- Visualización de estructura -- Generación de planes -- Selección de planificador -- Ejecución SHOP2 -- Ejecución Pyhop -- Exportación -- Exportar PDF -- Exportar Excel -- Exportar JSON -- Administración -- Dashboard administrativo -- Configuración de planificadores -- Requisitos no funcionales -- Interfaces externas -- Interfaces de usuario -- Software -- Comunicación -- Restricciones -- Restricciones técnicas -- Restricciones de negocio -- Anexo: Manual de usuario funcionario y usuario administrador -- Anexo: Matriz de impacto cruzado y resultados de evaluación de OI e IC en extensión universitaria -- Anexo: Ambiente de planificación en inteligencia artificial -- Descripción general -- Visión del sistema -- Objetivo principal -- Características principales -- Arquitectura del sistema -- Capas del sistema -- Capa de presentación -- Capa de aplicación -- Capa de procesamiento -- Capa de datos -- Stack tecnológico -- Parser BPMN -- SHOP2 simulator -- Pyhop engine -- Sistema de exportación -- Seguridad y rendimiento -- Medidas de seguridad -- Anexo: Guía para desarrollar BPMN a partir de proyectos de extensión universitaria -- Herramienta recomendada -- ¿Qué representa un proyecto en BPMN? -- Elementos mínimos que debe usar -- Uso de decisiones -- Creación y uso de subprocesos -- ¿Cuándo conviene usar un subproceso? -- Tipos recomendados para PlanProjU -- Cómo crear un subproceso en BPMN.io -- Reglas de consistencia para subprocesos -- Uso de roles -- Reglas clave para que PlanProjU funcione correctamente -- Cómo guardar el archivo -- Qué hará PlanProjU con su BPMN -- Anexo: Cuestionario de validación de la plataforma PlanProjU -- Enlace de análisis de resultados -- Sección 1 – Perfil del participante -- Sección 2 – Evaluación del sistema -- Dimensión D1 – Usabilidad del sistema (SUS) -- Dimensión D2 – Evaluación global del sistema -- Anexo: Cuestionario de validación de la plataforma PlanProjU -- ReferenciasDoctoradoLa presente investigación, se desarrolló bajo el enfoque de la metodología DSR (design science research), que se caracteriza por contener un flujo de conocimiento, que agrupa las contribuciones al conocimiento realizado por la investigación. También incluye un procedimiento que consiste en aproximación al problema de investigación, sugerencias, desarrollo, evaluación y conclusión. 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