VSFS:N_ZI Knowledge Engineering - Course Information
N_ZI Knowledge Engineering
University of Finance and AdministrationSummer 2021
- Extent and Intensity
- 2/2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- prof. Ing. Petr Berka, CSc. (seminar tutor)
Ing. Renata Janošcová, Ph.D. (seminar tutor) - Guaranteed by
- prof. Ing. Petr Berka, CSc.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Ivana Plačková - Timetable of Seminar Groups
- N_ZI/vAPH: Fri 5. 2. 14:00–15:30 S14, 15:45–17:15 S14, Fri 19. 2. 14:00–15:30 S14, 15:45–17:15 S14, Sat 6. 3. 14:00–15:30 S14, 15:45–17:15 S14, Fri 19. 3. 14:00–15:30 S14, 15:45–17:15 S14, P. Berka
- Prerequisites
- There are no prerequisites for this course.
- Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives
- Intelligent systems are used to solve complex problems that require human intelligence. On a very general level, intelligent systems combine knowledge-based and model-based approaches to achieve human-like abilities. The goal of the course is to introduce principles of knowledge-based methods in artificial intelligence.
- Learning outcomes
- At the end of the course students should be able to:
- explain basic approaches to problem solving using state space
- describe different decision strategies
- explain knowledge representation and reasoning methods
- describe methods for expressing uncertainty
- explain basic principles of machine learning and adaptation
- describe approaches to building agent systems - Syllabus
- - State space search
- - Game theory
- - Knowledge representation
- - Knowledge processing
- - Ucertainty reprezentation
- - Decision strategies
- - Uncertainty processing
- - Machine learning
- - Learning and adaptation
- - Multiagent systems
- Literature
- Russell S., Norvig P.: Artificial Intelligence. A Modern Approach. 3. edition, Pearson, 2009
- Berka, Petr: Inteligentní Systémy, VŠE Praha, 2008. ISBN 978-80-245-1436-9
- Teaching methods
- - lectures and seminars in full-time study,
- tutorials in part-time study,
- case study on application of artificial intelligence
Lectures and seminars in full-time study; tutorials in part-time study; compulsory seminar participation is 75% in full-time study, compulsory tutorial participation is 50% in part-time study - Assessment methods
- - written final test consisting of unstructured questions (min 60% points)
- homeworks from seminars
- case study on application of artificial intelligence - Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course can also be completed outside the examination period.
Information on the extent and intensity of the course: 16 hodin KS/semestr.
- Enrolment Statistics (Summer 2021, recent)
- Permalink: https://is.vsfs.cz/course/vsfs/summer2021/N_ZI