13M114IS - Intelligent Services and Systems

Course specification
Course title		Intelligent Services and Systems
Acronym		13M114IS
Study programme		Electrical Engineering and Computing
Module
Type of study		master academic studies
Lecturer (for classes)		professor PhD Boško Nikolić professor PhD Dražen Drašković
Lecturer/Associate (for practice)		asst. professor PhD Vladimir Jocović asst. MA Adrian Milaković, electrical and computer engineer
Lecturer/Associate (for OTC)		asst. professor PhD Vladimir Jocović asst. MA Adrian Milaković, electrical and computer engineer
ESPB		6.0	Status	elective
Condition		/
The goal		Introduce students to the basic concepts and techniques of artificial intelligence, intelligent services and expert systems. During the course, students will study the implementation of the popular models of these types of applications.
The outcome		Students will be able to recognize a problem that belongs to the field of artificial intelligence and expert systems, and based on their knowledge apply the most appropriate and most effective method for its solution.
Contents
URL to the subject page		http://ri4es.etf.rs/
Contents of lectures		Search strategies: algorithms, performance, efficiency, complexity. Game theory - Minimax algorithm, alpha-beta pruning, negamax, negascout. First-order logic. Production systems. Planning - types and the problem. Knowledge and reasoning in uncertain environment. Bayesian networks. Problem-solving strategies. Introduction to machine learning, linear regression, K-nearest neighbor, decision trees.
Contents of exercises		Visual simulations of theoretical problems. Solving and demonstrations of practical tasks. Homeworks in which it is necessary to implement intelligent agents.
Literature
"Artificial Intelligence - A Modern Approach", S. Russel, P. Norvig (publisher: Pearson; 3 edition; 2009) "Collection of problems from Expert Systems", D. Bojić, M. Gligorić, B. Nikolić, Akademska misao, Belgrade, 2009
Number of hours per week during the semester/trimester/year
Lectures	Exercises	OTC	Study and Research	Other classes
2	2	1
Methods of teaching		Lectures, presentations, practical exercises, individual work on homeworks, laboratory exercises with visual simulations
Knowledge score (maximum points 100)
Pre obligations		Points	Final exam	Points
Activites during lectures		0	Test paper	40
Practical lessons		20	Oral examination	0
Projects		0
Colloquia		40
Seminars		0