B_ES Expert Systems

University of Finance and Administration
Summer 2022
Extent and Intensity
2/0/0. 3 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. Ing. Petr Berka, CSc. (seminar tutor)
Guaranteed by
Ing. Renata Janošcová, Ph.D.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Ivana Plačková
Timetable of Seminar Groups
B_ES/pAPH: Wed 10:30–11:14 E007KC, Wed 11:15–12:00 E007KC, except Wed 9. 2., except Wed 9. 3. ; and Wed 9. 2. 12:15–13:45 S13, Wed 16. 3. 8:45–10:15 E007KC, P. Berka
B_ES/vAPH: Sat 5. 2. 14:00–15:30 E225, 15:45–17:15 E225, Sat 19. 2. 14:00–15:30 E228, 15:45–17:15 E228, Sat 19. 3. 9:45–11:15 E304, 11:30–13:00 E304, 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
Students will get familiar with basic principles of knowledge-based systems with main focus on rule-based expert systems of the first generation.
At the end of the course students should be able to:
- assess application areas of expert systems,
- describe the architecture and functionality of expert systems,
- design applications of rule-based expert systems.
Learning outcomes
Upon successful completion of this course, students will be able to:
- explain basic principles of expert systems
- explain knowledge reprezentation methods used in expert systems
- explain methods of inference used in expert systems
- assess the suitability of expert system application for a given area
- design and implement knowledge base for a given task
Syllabus
  • 1. Research areas in artificial intelligence
  • 2. State space search
  • 3. Types and architecture of expert systems
  • 4. Concultations with expert system NEST
  • 5. Knowledge representation in expert systems
  • 6. Inference and reasoning in expert systems
  • 7. Building knowledge bases for expert system NEST
  • 8. Uncertainty processing in expert systems
  • 9. Life cycle of expert systems and knowledge base creation
  • 10. Perspectives of knowledge engineering
  • 11. Creating an application using expert system NEST
  • 12. Test
Literature
    required literature
  • BERKA, Petr, Petr JIRKŮ and Jiřina VEJNAROVÁ. Expertní systémy (Expert systems). Praha: VŠE, 1998. skripta. ISBN 80-7079-873-4. info
    recommended literature
  • KELEMEN, J., Petr BERKA and ET AL. Pozvanie do znalostnej spoločnosti. Bratislava: Iura Edition – Wolters Kluwer, 2007, 265 pp. ISBN 978-80-8078-149-1. info
  • BERKA, Petr and J KELEMEN. On the Development of the Knowledge and Information Technology. In Knowledge in Context. Bratislava: Iura edition, 2010. ISBN 978-80-8078-339-6. info
    not specified
  • Akerkar, R., Sajja, P.: Knowledge-Based Systems.Jones & Bartlett Learning, 2009
Teaching methods
- lectures and seminars in full-time study,
- tutorials in part-time study,
- case study of an expert system application
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 of an expert system application
Language of instruction
Czech
Follow-Up Courses
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: 12 hodin KS/semestr.
The course is also listed under the following terms Summer 2008, Winter 2008, Summer 2009, Winter 2009, Winter 2010, Winter 2011, Winter 2012, Winter 2013, Winter 2014, Winter 2015, Winter 2016, Winter 2017, Winter 2018, Winter 2019, Winter 2020, Summer 2023, Summer 2024, Summer 2025.
  • Enrolment Statistics (Summer 2022, recent)
  • Permalink: https://is.vsfs.cz/course/vsfs/summer2022/B_ES