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Disciplina asociada:Inteligencia Artificial |
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Escuela:
Ingeniería y Ciencias
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Departamento Académico:
Computación
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Programas académicos: |
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Requisitos:No tiene. |
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Equivalencia:IA4002 ; CS5041 |
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Intención del curso en el contexto general del plan de estudios: |
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Curso avanzado que tiene la intención de proporcionarle al alumno las técnicas y algoritmos necesarios para el desarrollo de sistemas basados en lógica difusa y probabilidad y estadística. Como resultado de su aprendizaje, el alumno será capaz de desarrollar sistemas inteligentes para ambientes inciertos. |
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Objetivo general de la Unidad de Formación: |
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Al finalizar el curso el alumno será capaz de comprender las principales técnicas y algoritmos de Inteligencia Artificial para ambientes con incertidumbre, comprender las técnicas probabilistas para la toma de decisiones simples y secuenciales, comprender la modelación Bayesiana, sus procesos de inferencia y aprendizaje y comprender la teoría de lógica difusa. Además será capaz de aplicar estos conocimientos para el desarrollo de sistemas de razonamiento y aprendizaje utilizando estas técnicas en ambientes inciertos. |
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Técnica didáctica sugerida: |
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| No especificado | |||||
Bibliografía sugerida: |
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LIBROS DE TEXTO: * Russell, Stuart J. (Stuart Jonathan), Artificial intelligence: A modern approach, 2nd. Edition, New Jersey : Englewood Cliffs, N. J.: Prentice Hall/Pearson Education, 2003, eng, 0137903952 * Jensen, Finn V., Bayesian networks and decision graphs, 2nd. Edition, New York : New York: Springer, 2007, eng, 0387682813, 9780387682815 * Wang, Li-Xin, A course in fuzzy systems and control, Upper Saddle River, N. J.; México: Prentice Hall PTR, 1997, 0135408822 (encuadernado), 9780135408827 (encuadernado) LIBROS DE CONSULTA: * Sutton, Richard S., Reinforcement learning: An introduction, Cambridge, Mass.: MIT Press, 1998, 0262193981 (papel alcalino), 9780262193986 (papel alcalino) * Pearl, Judea, Probabilistic reasoning in intelligent systems: Networks of plausible inference, Revised second printing., California : San Francisco, Calif.: Morgan Kaufmann Publishers, 1988, eng, 1558604790 |
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Perfil del Profesor: |
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(110102)Doctorado en Inteligencia Artificial /Robótica ; (110701)Doctorado en Ciencias Computacionales ; (141001)Doctorado en Ingeniería Eléctrica/Electrónica y Comunicaciones CIP: 110102, 110701, 141001 |
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Discipline:Artificial Intelligence |
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School:
Engineering and Sciences
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Academic Department:
Computing
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Programs: |
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Prerequisites:None. |
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Equivalences:IA4002 ; CS5041 |
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Course intention within the general study plan context: |
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This advanced course provides the student with the basic techniques and algorithms required to develop systems based on fuzzy logic and probability and statistics. Learning outcome: the student will be able to develop intelligent systems for uncertain environments. |
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Course objective: |
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| On completion of the course, students will be able to understand the main Artificial intelligence techniques and algorithms for uncertain environments; they will understand probabilistic techniques for simple and sequential decision making; Bayesian modeling, inference and learning processes, and fuzzy logic theory. In addition, they will be able to apply this knowledge to developing reasoning and learning systems, utilizing these techniques in uncertain environments. | |||||
Teaching and learning tecniques: |
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| Not Specified | |||||
Suggested Bibliography: |
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TEXT BOOKS: * Russell, Stuart J. (Stuart Jonathan), Artificial intelligence: A modern approach, 2nd. Edition, New Jersey : Englewood Cliffs, N. J.: Prentice Hall/Pearson Education, 2003, eng, 0137903952 * Jensen, Finn V., Bayesian networks and decision graphs, 2nd. Edition, New York : New York: Springer, 2007, eng, 0387682813, 9780387682815 * Wang, Li-Xin, A course in fuzzy systems and control, Upper Saddle River, N. J.; México: Prentice Hall PTR, 1997, 0135408822 (encuadernado), 9780135408827 (encuadernado) BOOKS FOR CONSULTATION: * Sutton, Richard S., Reinforcement learning: An introduction, Cambridge, Mass.: MIT Press, 1998, 0262193981 (papel alcalino), 9780262193986 (papel alcalino) * Pearl, Judea, Probabilistic reasoning in intelligent systems: Networks of plausible inference, Revised second printing., California : San Francisco, Calif.: Morgan Kaufmann Publishers, 1988, eng, 1558604790 |
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Academic credentials required to teach the course: |
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(110102)Doctoral Degree in Artificial Intelligence/Robotics and (110701)Doctoral Degree in Computational Sciences and (141001)Doctoral Degree in Electrical Engineering/ Electronics and Communications CIP: 110102, 110701, 141001 |
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