FPF:UIIABP0029 Knowledge-Based & Expert Sys. - Course Information
UIIABP0029 Knowledge-Based and Expert Systems
Faculty of Philosophy and Science in OpavaWinter 2023
- Extent and Intensity
- 2/0/0. 4 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Ing. Jiří Blahuta, Ph.D. (lecturer)
- Guaranteed by
- Ing. Jiří Blahuta, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava - Timetable
- Tue 11:25–13:00 B2
- Prerequisites
- Artificial Intelligence
- 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
- Computer science and English (programme FPF, In-An-bp)
- Course objectives
- The course introduces students, in succession of the course Artificial Intelligence, into the issues of applications of artificial intelligence in the field of knowledge-based and expert systems.
- Learning outcomes
- Students will be able to:
- define basic terms like a finding, knowledge, their computer representation
- define terms knowledge-based and expert system
- describe the architecture and individual modules of the knowledge-based and expert system
- thoroughly describe the function of the inference engine, including the rule selection problem and heuristics
- explain the issue of quality, evaluation, and testing of the knowledge-based system
- be versed in the field of knowledge engineering
- apply the fuzzy approach in the development of the knowledge-based systems - Syllabus
- 1. History of expert and knowledge-based systems
- 2. Knowledge and the representation of knowledge
- 3. Determinism, nondeterminism, Knowledge-based/expert systems
- 4. Knowledge rule-base, fact base, basis of the inference engine
- 5. Inference engine
- 6. Other modules of the knowledge-based/expert system
- 7. Knowledge engineering
- 8. Fuzzy expert systems
- 9. Quality and evaluating of the expert systems
- Literature
- required literature
- CASTILLO, Enrique et. al. and CASTILLO, Enrique et. al. Expert systems and probabilistic network models. New York: Springer, 2012. ISBN 978-1-4612-7481-0. info
- recommended literature
- Jozef Kelemen, Aleš Kubík, Imrich Lenharčík, Peter Mikulecký,. Tvorba expertních systémů v prostředí CLIPS - podrobný průvodce. ISBN 80-7169-501-7. info
- MAŘÍK, V. a kol. and MAŘÍK, V. a kol. Umělá inteligence (1-6). Praha,: Academia, 2013. info
- KOMNINOS, Nicos. Intelligent cities: innovation, knowledge systems, and digital spaces. SponPress, 2012. ISBN 0-415-27718-3. info
- KOMNINOS, Nicos. Intelligent cities: innovation, knowledge systems, and digital spaces. SponPress, 2012. ISBN 0-415-27718-3. info
- KELEMEN, J., LIDAY, M. Expertné systémy pre prax. Bratislava, 1996. info
- POPPER, M., KELEMEN, J. Expertné systémy. Bratislava, 1989. info
- Teaching methods
- Lecture
- Assessment methods
- Oral exam in the scope of discussed topics.
- Language of instruction
- Czech
- Further Comments
- Study Materials
- Enrolment Statistics (Winter 2023, recent)
- Permalink: https://is.slu.cz/course/fpf/winter2023/UIIABP0029