638-3010/03 – Methods of Artificial Intelligence (MUI)

Gurantor department	Department of Automation and Computing in Industry	Credits	6
Subject guarantor	doc. Ing. Jiří David, Ph.D.	Subject version guarantor	doc. Ing. Jiří David, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	2	Semester	winter
		Study language	Czech
Year of introduction	2019/2020	Year of cancellation
Intended for the faculties	FMT	Intended for study types	Follow-up Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
DAV47	doc. Ing. Jiří David, Ph.D.
SVO0120	Ing. Petra Svobodová
TOM0194	Ing. Antonín Tomeček

Extent of instruction for forms of study
Form of study	Way 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

Lectures
Tutorials
Project work

Summary

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

Písemný test a ústní zkoušení.

E-learning

Other requirements

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

Prerequisities

Subject has no prerequisities.

Co-requisities

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: 2019/2020 Winter semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Credit and Examination	Credit and Examination	100 (100)	51
Credit	Credit	35	25
Examination	Examination	65	26	3

Mandatory attendence participation: Testing

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic year	Programme	Branch/spec.	Zaměření	Form	Study language	Tut. centre	Year	Type of duty
2021/2022	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	P	Czech	Ostrava	2	Compulsory	study plan
2021/2022	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		P	Czech	Ostrava	2	Compulsory	study plan
2021/2022	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		K	Czech	Ostrava	2	Compulsory	study plan
2021/2022	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	K	Czech	Ostrava	2	Compulsory	study plan
2020/2021	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		K	Czech	Ostrava	2	Compulsory	study plan
2020/2021	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	K	Czech	Ostrava	2	Compulsory	study plan
2020/2021	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		P	Czech	Ostrava	2	Compulsory	study plan
2020/2021	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	P	Czech	Ostrava	2	Compulsory	study plan
2019/2020	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	P	Czech	Ostrava	2	Compulsory	study plan
2019/2020	(N0413A270002) Quality Management and Control of Industrial Systems	(S03) Intelligent Control Systems in Industry	IŘ	K	Czech	Ostrava	2	Compulsory	study plan
2019/2020	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		P	Czech	Ostrava	2	Compulsory	study plan
2019/2020	(N0413A270002) Quality Management and Control of Industrial Systems	(S02) Economics and Management in Industry		K	Czech	Ostrava	2	Compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

2021/2022 Winter

2020/2021 Winter