DegreeProgramme 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

1. An Introduction of AI
2. Representation I. Introduction
3. Representation II. Production Systems
4. Search I. Introduction 
5. Search II. Blind
6. Search III. Heuristic2
7. Reasoning under Uncertainty I. Introduction.
8. Reasoning under Uncertainty II. Bayesian Inference.
9. Reasoning under Uncertainty III. Bayesian Networks.
10. Reasoning under Uncertainty IV. Markov Models.
11. Reasoning under Uncertainty V. Fuzzy Logic I.
12. Reasoning under Uncertainty VI. Fuzzy Logic II.
13. Applied Artificial Intelligence I
14. 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.