Universitatea Babeş-Bolyai Cluj-Napoca
Facultatea de Matematică şi Informatică
Ciclul de studii: Licenţă
Domeniul: Informatică
Programul de studii: Informatică - în limba engleză
Limba de predare: Engleză

SYLLABUS

I. General data
Code	Subject	
MII0001	Artificial Intelligence	

Semester	Hours: C+S+L+P	Category	Status	
4	2+1+1+0	speciality	compulsory	

II. Full status faculty members
Name and	Scientific	Didactic	Chair	Type of activity	
surname	title	title		C	S	L	
GROSAN Crina Daniela	Ph.D.	Lect.	Computer Science	*			

Associated faculty members
Name and	Scientific	Institution	Type of	Type of activity	
surname	title		position	C	S	L	

III. Course objectives
Supply an introduction to the field of AI.
Give the basic notion, techniques and algorithms of AI.
Supply the background for advanced AI courses.	

IV. Course contents
1. Introduction to AI
2. Solving problems by search
3. Knowledge representation and reasoning
4. Fuzzy systems
5. Neural networks
6. Evolutionary computation
7. Swarm intelligence	

V. Bibliography
DUMITRESCU,D.,B Lazzerini,Evolutionary Computation, CRC Press, New York, Boca Raton, 2000
DUMITRESCU,D.,B Lazzerini,Fuzzy Sets and treir Application in Training and Clustering , CRC Press, New York, Boca Raton, 2000
DUMITRESCU, D.,Principiile  Inteligentei artificiale,  Editura Albastra, Cluj,2000.
DUMITRESCU, D.,Principiile  teoriei clasificarii,  Editura Academiei, Bucuresti,2000.
DUMITRESCU, D.,Algoritmi genetici si strategii evolutive. Aplicatii in Inteligenta      Artificiala,  Editura Albastra, Cluj,2000.
DUMITRESCU, D., Inteligenta artificiala,  Univ. "Babes-Bolyai", 1995.
DUMITRESCU, D., Modele conexioniste in Inteligenta Artificiala, Univ. "Babes-Bolyai", 1995.
DUMITRESCU, D., Retele Neuronale, Teora, 1997
MALITA, M., Bazele matematice ale Inteligentei Artificiale, Ed.Tehnica, 1988.
PATRIDGE, D., Artificial Intelligence. Aplications in the future of software engineering, Ellis Harwood Series in A.I., John Wiley & Sons, New York 1986.
RICH, E. Artificial Intelligence, Mc.Graw Hill, 1989.
WINSTON, P., Inteligenta artificiala, Ed.Tehnica, 1980.
GOLDBERG, D. E., Genetic Algorithm. Addison-Wesley, Reading, 1989.	

VI. Thematic of didactic activities per weeks
Introduction to AI
Problem solving as search
Problem spaces
Uninformed search
Breadth first search
Depth first search
Limited depth first search
Iterative-deepening search
Uniform cost search
Problem solving as search
Informed search
Heuristic search
Best-first search 
Greedy 
A* algorithm 
A* variants
Local search
Simulated annealing
Hill climbing
Game playing
Minimax search
Alpha-beta pruning
Knowledge representation and reasoning
Knowledge based systems
Rule based systems
Uncertainty management in rule based systems. 
Fuzzy systems
Neural networks
Single layer neural networks
Perceptron model 
Neural networks
Multi-layer neural networks
Backpropagation learning
Hopfield networks
Self organizing maps
Evolutionary computation
Evolutionary algorithms
Evolutionary Computation
Evolutionary strategies
Evolutionary programming
Genetic programming
Swarm intelligence
Particle swarm optimization
Ant Colonies optimization	

VII. Didactic methods used

VIII. Assessment
The final mark will be given based on:
40% Lab assignment
50% Written exams (THERE WILL BE 3 WRITTEN EXAM ONE HOUR EACH DURING THE SEMESTER; EACH OF THEM WEIGTHS 20%)
10% Seminar project	

IX. Additional references

	Dean,							Chair head,

	Date,							Course responsible,
								Lect. GROSAN Crina Daniela, Ph.D.