654-3010/02 – Methods of Artificial Intelligence (MUI)

Gurantor departmentDepartment of Industrial Systems ManagementCredits6
Subject guarantordoc. Ing. Jiří David, Ph.D.Subject version guarantordoc. Ing. Jiří David, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageEnglish
Year of introduction2022/2023Year of cancellation
Intended for the facultiesFMTIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
DAV47 doc. Ing. Jiří David, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 3+2
Part-time Credit and Examination 16+0

Subject aims expressed by acquired skills and competences

Student will be able to formulate and suggest the solution with utilization the instruments artificial inteligence. Student will be able to create the knowledge base for the intelligent controller. Student will be able to analyze the problems technical application in field the engineering cybernetics with utilization the instruments artificial inteligence. Student will be able to formulate and suggest the solution problems with utilization Matlab toolboxs Fuzzy Logic, Neural Network and Genetic Algorithm.

Teaching methods

Project work


Subjekt put mind to the questions artificial inteligence. Students do one's homework the control models on platform the artificial inteligence (qualitative and semi-qualitative models, fuzzy models, the knowledge-based systém,systems of neural network and genetic algorithm).

Compulsory literature:

RUSSELL, S. and P. NORVIG. Artificial Intelligence: A Modern Approach. New Jersey: Prentice Hall, 2002. ISBN 0-13-790395-2. BOURBAKIS, N. G. Artificial Intelligence: Methods and Applications. World Scientific, 1992. ISBN: 978-981-02-1057-1. FORSYTH, R. Expert systems: principles and case studies. New York: Chapman and Hall, 1989. ISBN: 9780412304606.

Recommended literature:

BOURBAKIS, N. G. Artificial intelligence and automation. London: World Scientific, 1998. ISBN: 978-9810226374. NILSSON, N. J. Artificial Intelligence: a new synthesis. Burlington: Morgan Kaufmann Publishers, Inc.;, 1998. ISBN: 978-1558604674.

Way of continuous check of knowledge in the course of semester

Written and oral examination


Other requirements

Getting to know the practical solution of problems with the use of artificial intelligence methods.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Control as a informative incidence, activity and process. 2. Determination theory modelling and artificial intelligence. 3. Qualitative models. 4. Semiqualitative models. 5. Fuzzy model, introduction to fuzzy models. 6. Fuzzy multiple theory. 7. More value logic and language model. 8. Fuzzy systems 9.Strategy fuzzification, strategy defuzzification. 10. Expert systems, definition and architecture expert systems. 11. Knowledge base, inferential mechanism, interpretation answer expert systems. 12. Expert systems and control. 13. Introduction to the neuronal systems. 14. Neuronal networks. 15. Genetic algorithms.

Conditions for subject completion

Full-time form (validity from: 2022/2023 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 35  25
        Examination Examination 65  26
Mandatory attendence parzicipation: Testing

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2022/2023 (N0413A270003) Quality Management and Control of Industrial Systems P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
FMT + Nanotechnology 2022/2023 Full-time English Optional 600 - Faculty of Materials Science and Technology - Dean's Office stu. block