Oct 26, 2020   10:52 p.m. Demeter
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Course syllabus UI_B - Artificial Intelligence (FIIT - WS 2020/2021)


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University:
Slovak University of Technology in Bratislava
Faculty:
Course unit code:
UI_B
Course unit title:
Artificial Intelligence
Mode of delivery, planned learning activities and teaching methods:
lecture
2 hours weekly (on-site method)
laboratory/construction practice
2 hours weekly (on-site method)
project/semestral paper
1 hour weekly (on-site method)

 
Credits allocated:
6
 
Recommended semester/trimester:
Informatics - bachelor (compulsory), 3. semester
Informatics (conversion programme with a foundation year) - bachelor (compulsory), 5. semester
Information Security (conversion programme with a foundation year) - bachelor (compulsory), 5. semester
Level of study:
-- item not defined --
Prerequisites for registration:
none
 
Assesment methods:
Conditions for admission to final exam:
Elaboration and submission of all the required assignments.
Obtain at least 4 points for the 1st assignment and at least 6 points for each of the remaining three assignments.
Obrain at least 38 points for all assignments in total.
Conditions for a passing grade:
Earning a sufficient number of points (according to the study code) for the following:
assignments: totally 70,
final exam: totally 30.
 
Learning outcomes of the course unit:
To acquire deeper knowledge of principles of artificial intelligence. To understand principles of symbolic and subsymbolic artificial intelligence in a broader context of informatic sciences. To master techniques, methods, structures for problem solving that are based on computation processes involving representation of knowledge. To acquire practical experience with designing intelligent agents.
 
Course contents:
1. Artificial intelligence, its contents, methodology.
2. Problem solving.
3. State space, search for solution.
4. Uninformed search.
5. Heuristic search.
6. Games problem solving.
7. Machine learning.
8. Neural networks and evolutionary algorithms.
9. Mathematical logic for artificial intelligence.
10. Knowledge representation.
11. Uncertain knowledge and its representation.
12. Planning.
13. Multiagent systems.
 
Recommended or required reading:
Basic:
NÁVRAT, P. -- BIELIKOVÁ, M. -- BEŇUŠKOVÁ, Ľ. -- KAPUSTÍK, I. -- UNGER, M. Umelá inteligencia. Bratislava : STU v Bratislave, 2002. 393 p. ISBN 80-227-1645-6.
KOZÁK, Š. Inteligentné vnorené systémy. In KVASNIČKA, V. -- POSPÍCHAL, J. -- KOZÁK, Š. -- NÁVRAT, P. -- PAROULEK, P. Artificial Intelligence and Cognitive Science. Vydavateľstvo STU v Bratislave, 2009, p. 139--193. ISBN 978-80-227-3080-8.
RUSSEL, S J. -- NORVIG, P. Artificial intelligence a modern approach. Upper Saddle River : Prentice Hall, 2003. 1080 p. ISBN 0-13-080302-2.
KVASNIČKA, V. -- POSPÍCHAL, J. -- TIŇO, P. Evolučné algoritmy. Bratislava : STU v Bratislave, 2000. 215 p. ISBN 80-227-1377-5.
KVASNIČKA, V. -- BEŇUŠKOVÁ, Ľ. -- POSPÍCHAL, J. -- FARKAŠ, I. -- TIŇO, P. -- KRÁĽ, A. Úvod do teórie neurónových sietí. Bratislava : IRIS-Knižní klub, 1997. 285 strany. ISBN 80-88778-30-1.

 
Language of instruction:
-- item not defined --
 
Notes:
 
Courses evaluation:
Assessed students in total: 2082

A
B
C
D
E
FX
7,6 %
17,1 %
30,2 %25,1 %
13,3 %
6,7 %
Name of lecturer(s): Ing. Ivan Kapustík (instructor) - slovak
Ing. Lukáš Kohútka, PhD. (examiner, instructor, lecturer, person responsible for course) - slovak
Ing. Boris Slíž (instructor) - slovak
Ing. Juraj Vincúr (instructor) - slovak
 
Last modification:
17. 9. 2020
Supervisor:
Ing. Lukáš Kohútka, PhD. and programme supervisor


Last modification made by RNDr. Marta Gnipová on 09/17/2020.

Type of output: