N_ZI Knowledge Engineering

University of Finance and Administration
Summer 2024
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Guaranteed by
Ing. Renata Janošcová, Ph.D.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Ivana Plačková
Prerequisites
There are no prerequisites for this course.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
Intelligent systems are used to solve complex problems that require human intelligence. On a very general level, intelligent systems combine knowledge-based and model-based approaches to achieve human-like abilities. The goal of the course is to introduce principles of knowledge-based methods in artificial intelligence.
Learning outcomes
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
  • - Introduction and history of AI
  • - State space search
  • - Game theory
  • - Knowledge representation
  • - Knowledge processing
  • - Ucertainty reprezentation
  • - Decision strategies
  • - Uncertainty processing
  • - Machine learning
  • - Learning and adaptation
  • - Multiagent systems
Literature
  • Berka, Petr: Inteligentní Systémy, VŠE Praha, 2008. ISBN 978-80-245-1436-9
  • 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 artificial intelligence
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)
- homeworks from seminars
- case study on application of artificial intelligence (referát)
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: 16 hodin KS/semestr.
The course is also listed under the following terms Summer 2021, Summer 2022, Summer 2023.
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