VSFS:N_MaTR Mathematical Decision Theory - Course Information
N_MaTR Mathematical Decision Theory
University of Finance and AdministrationSummer 2017
- Extent and Intensity
- 2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- prof. Ing. Petr Berka, CSc. (seminar tutor)
- Guaranteed by
- prof. Ing. Petr Berka, CSc.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Ing. Barbora Ptáčková - Timetable of Seminar Groups
- N_MaTR/vAPH: Fri 10. 2. 15:45–17:15 S14, 17:30–19:00 S14, Fri 24. 2. 17:30–19:00 S14, Sat 11. 3. 9:45–11:15 S14, 11:30–13:00 S14, P. Berka
- Prerequisites
- There are no prerequisites for this course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme VSFS, N-INF) (2)
- Course objectives
- The goal of the course is to introduce principles of decision-making in intelligent systems.
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
- - Blind state space search
- - Heuristic state space search
- - Game theory
- - Knowledge representation
- - Knowledge processing
- - Ucertainty reprezentation
- - Decision strategies
- - Uncertainty processing
- - Machine learning
- - Learning and adaptation
- - Reactive agents
- - Deliberative agents
- Literature
- required literature
- Berka, Petr: Inteligentní Systémy, VŠE Praha, 2008. ISBN 978-80-245-1436-9
- not specified
- Russell S., Norvig P.: Artificial Intelligence. A Modern Approach. 3. edition, Pearson, 2009
- Teaching methods
- - lectures and seminars in full-time study,
- tutorials in part-time study,
- case study on application of intelligent systems
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)
- case study on application of intelligent systems - 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: 10 hodin KS/semestr.
- Enrolment Statistics (Summer 2017, recent)
- Permalink: https://is.vsfs.cz/course/vsfs/summer2017/N_MaTR