This course is taught only by this group.
Degree Programme
Other Resources
Coordinator
Competences
Abstraction (PO a)
Problem solving (PO c)
Capacity to apply theoretical concepts (PO c)
Evaluation based on multiple Theoretical IA tasks (PO a)
Students should use different IA techniques, compare them through experiments, and analyze the results (PO b)
Students should apply the right and appropriate AI technique and parameters to solve a task (objective) (PO c)
Students should work on the homeworks in teams (PO d)
Students are required to use AI tools and provide solutions to real-world problems through computer engineering (PO e)
Study Program
An Introduction of AI
Representation I. Introduction
Representation II. Production Systems
Search I. Introduction
Search II. Blind
Search III. Heuristic2
Reasoning under Uncertainty I. Introduction.
Reasoning under Uncertainty II. Bayesian Inference.
Reasoning under Uncertainty III. Bayesian Networks.
Reasoning under Uncertainty IV. Markov Models.
Reasoning under Uncertainty V. Fuzzy Logic I.
Reasoning under Uncertainty VI. Fuzzy Logic II.
Applied Artificial Intelligence I
Applied Artificial Intelligence II
Group
Bachelor's Degree: Computer Science and Engineering (Plan 2008)
Field: Engineering. (Colmenarejo)
Field: Engineering. (Leganés)
Bachelor's Degree: Computer Science and Engineering (Plan 2011)
Field: Engineering. (Colmenarejo)
Field: Engineering. (Leganés)
Bibliography
D. Borrajo, N. Juristo, V. Martínez-Orga, J. Pazos. Inteligencia Artificial ¿ Métodos y Técnicas. Editorial Centro de estudios Ramón Areces. Madrid 1997.
Javier Carbó, RAfael MArtínez Y josé MAnuel Molina. Desarrollo de Sistemas Basados en el Conocimiento. CLIPS y FuzzyCLIPS. Sánchez Torres 2005.
S. Russell, P. Norvig. Inteligencia Artificial ¿ Un Enfoque Moderno (2ª ed.). Editorial Prentice Hall Hispanoamericana. 2003.