"Babes-Bolyai" University of Cluj-Napoca
Faculty of Mathematics and Computer Science

Artificial intelligence
Code
Semes-
ter
Hours: C+S+L
Credits
Type
Section
MI017
7
2+1+1
6
compulsory
Informatică
MI017
7
2+0+2
6
optional
Matematică-Informatică
MI017
7
2+1+1
6
optional
Matematică-Informatică
MI017
6
2+1+0
9
compulsory
Tehnologie Informatica
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