UIIABP0029 Knowledge-Based and Expert Systems

Faculty of Philosophy and Science in Opava
Winter 2021
Extent and Intensity
2/0/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
RNDr. Miroslav Langer, Ph.D. (lecturer)
Mgr. Daniel Valenta, Ph.D. (lecturer)
Guaranteed by
Ing. Jiří Blahuta, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable
Mon 18:05–19:40 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
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
The course is also listed under the following terms Winter 2020, Winter 2022, Winter 2023, Winter 2024.
  • Enrolment Statistics (Winter 2021, recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2021/UIIABP0029