Artificial intelligence |
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Teaching Staff in Charge |
Prof. DUMITRESCU Dan Dumitru, Ph.D., ddumitr@cs.ubbcluj.ro Lect. SOOS Anna, Ph.D., asoos@math.ubbcluj.ro |
Aims |
Supply an introduction to the field of AI.
Give the basic notion, techniques ans algorithms of AI. Suplly the background for advanced AI courses. |
Content |
1. Logical-symbolic paradigm of AI
2. Problem solving techniques 3. Knowledge representation in AI 4. Learning in AI systems 5. Conectionism 6. Perceptron model 7. Learning by LMS 8. Associative networks 9. Hoppfield model 10. Back propagation |
References |
1. Dumitrescu, D., Inteligenta artificiala, Lito. Univ. "Babes-Bolyai", 1995.
2. Dumitrescu, D., Modele conexioniste in Inteligenta Artificiala, Univ. "Babes-Bolyai", 1995. 3. Georgescu, I., Inteligenta artificiala, Ed. Academiei, 1987. 4. Malita, M., Bazele matematice ale Inteligentei Artificiale, Ed.Tehnica, 1988. 5. Partridge, D., Artificial Intelligence. Aplications in the future of software engineering, Ellis Harwood Series in A.I., John Wiley & Sons, New York 1986. 6. Rich, E. Artificial Intelligence, Mc.Graw Hill, 1989. 7. Winston, P., Inteligenta artificiala, Ed.Tehnica, 1980. 8. Goldberg, D. E., Genetic Algorithm. Addison-Wesley, Reading, 1989. |
Assessment |