Course: Introduction to Artificial Intelligence

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Course title Introduction to Artificial Intelligence
Course code KRP/INUI1
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study 1
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Taufer Ivan, prof. Ing. DrSc.
  • Škrabánek Pavel, Ing. Ph.D.
Course content
1. Introduction (Introduction to AI, basic terms, AI segmentation) 2. Knowledge representation 3. State space and its searching 4. Quality Planning 5. Recognition 6. Computer learning 7. Planning 8. Fuzzy (Introduction, Fuzzy sets, Linguistic variables) 9. Fuzzy (Linguistic variables, Linguistic hedges, Fuzzy logic) 10. Fuzzy Applications (Fuzzy logic systems, Fuzzy control) 11. Expert Systems (ES) (Introduction, ES development history, Segmentation of ES, AI techniques used in ES). 12. Diagnostic ES (with heuristic knowledge, knowledge without uncertainties). 13. Diagnostic ES (with models), planning ES, ES from user point of view.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Methods of individual activities
Learning outcomes
The subjekt acquaints students with some branches of the artificial inteligence - the problem solution (providing a basic frame and methology of complex problems solution), the other parts are optimalization methods and genetic algorithms. The following part of the subject composes the problems of fuzzy sets, fuzzy logic, and building of fuzzy systems. The last part of the course is dedicated to expert systems.
Basic orientation in the artificial inteligence problems. Ability to use optimization methods, genetic algorithms, fuzzy systems building and orientation in expert system probleme.
Prerequisites
Knowledge of graph theory.

Assessment methods and criteria
Home assignment evaluation, Discussion

Execution of the final complex project comprising of different tasks from individual parts of the subject.
Recommended literature
  • BERKA, P. Expertní systémy. Praha: VŠE, 1998. ISBN 0-7079-873-4.
  • MAŘÍK, V., ŠTĚPÁNKOVÁ, O., LAŽANSKÝ, j. Umělá inteligence 1. Academia Praha, 2004. ISBN 80-200-0496-3.
  • MAŘÍK, V., ŠTĚPÁNKOVÁ, O., LAŽANSKÝ, j. Umělá inteligence 2. Academia Praha, 2003. ISBN 80-200-0504-8.
  • PROVAZNÍK, I., BARDOŇOVÁ, J. Expertní systémy - praktická cvičení. VUT Brno, 2000. ISBN 80-214-1768-4.
  • SIVANANDAM, S.N., SUMATHI, S. Introduction do Fuzzy Logic using MATLAB. Heidlbeg:Springer, 2007. ISBN 10-3-540-35780-7.
  • ŠKRABÁNEK, P. Základy umělé inteligence (elektronické učební texty. 2010.
  • VYSOKÝ, P. Fuzzy řízení. Praha: ČVUT, 1996.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Communication and Controlling Technology (2015) Category: Electrical engineering, telecommunication and IT 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information Technology (2015) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Process Control (2014) Category: Special and interdisciplinary fields - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Communication and Controlling Technology (2014) Category: Electrical engineering, telecommunication and IT 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Communication and Controlling Technology (2016) Category: Electrical engineering, telecommunication and IT 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Process Control (2016) Category: Special and interdisciplinary fields - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Process Control (2013) Category: Special and interdisciplinary fields - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information Technology (2014) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Process Control (2015) Category: Special and interdisciplinary fields - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information Technology (2016) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Winter