Técnicas de Inteligencia Artificial basadas en una integración de la lógica simbólica y no-simbólica

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Browsing Técnicas de Inteligencia Artificial basadas en una integración de la lógica simbólica y no-simbólica by Author "Negro, Pablo Ariel"
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    Artificial Intelligence techniques based on the integration of symbolic logic and deep neural networks : a systematic review of the literature
    (Iberoamerican Society of Artificial Intelligence (IBERAMIA), 2022-6) Negro, Pablo Ariel ; Pons, Claudia Fabiana
    Artificial Intelligence is tackled from two predominant but very different approaches: symbolic Artificial Intelligence, which is inspired by mathematical logic and is based on the manipulation of abstract linguistic representations, and non-symbolic Artificial Intelligence, which focuses on the construction of predictive mathematical models from large sample data sets. Significantly, the shortcomings of each of these approaches align with the strengths of the other, suggesting that an integration between them would be beneficial. A successful synthesis of symbolic and non-symbolic artificial intelligence would give us the advantages of both worlds. This work aims to identify and classify solutions and architectures that use applied Artificial Intelligence techniques, based on the integration of symbolic and non-symbolic logic (particularly machine learning with artificial neural networks), to provide a comprehensive, exhaustive and organized vision of the solutions available in the literature, making them the subject of a carefully designed and implemented SLR (Systematic Literature Review). The resulting technologies are discussed and evaluated from both perspectives: symbolic and non-symbolic Artificial Intelligence. The PICOC method (Population, Intervention, Comparison, Outputs, Context) plus Limits, which determine the scope of the search, has been used to define the research questions and analyze the results. From a total of 65 candidate studies found, 24 articles (37%) relevant to this study were selected. Each study also focuses on different application domains such as intelligent agents, image classification, theorem provers, cyber-security, image interpretation, mathematics, medicine, robotics and general application. Through the analysis of the selected works, it was possible to classify, organize and explain the different ways in which the deficiencies of non-symbolic Artificial Intelligence are addressed by proposals based on symbolic logic. The study also determined in which stages of the development process said proposals are applied. In addition, the study made it possible to determine which are the logic tools that are preferably applied, for each area and each domain. Although no clear architectural pattern has been found, efforts to find a general-purpose model that combines both worlds are driving trends and research efforts.
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    Extracción de reglas en redes neuronales feedforward entrenadas con lógica de primer orden
    (Sociedad Argentina de Informática (SADIO), 2023-10-20) Negro, Pablo Ariel ; Pons, Claudia Fabiana
    La necesidad de integración neural-simbólica se hace evidente a medida que se abordan problemas más complejos, y que van más allá de tareas de dominio limitadas como lo es la clasificación. Los métodos de búsqueda para la extracción de reglas de las redes neuronales funcionan enviando combinaciones datos de entrada que activan un conjunto de neuronas. Ordenando adecuadamente los pesos de entrada de una neurona, es posible acotar el espacio de búsqueda. Con base en esta observación, este trabajo tiene por objetivo presentar un método para extraer el patrón de reglas aprendido por una red neuronal entrenada feed-forward, analizar sus propiedades y explicar estos patrones a través del uso de lógica de primer orden (FOL).