SubjectsSubjects(version: 955)
Course, academic year 2019/2020
  
Applied Artificial Intelligence - M445014
Title: Aplikovaná umělá inteligence
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: winter
Points: winter s.:4
E-Credits: winter s.:4
Examination process: winter s.:
Hours per week, examination: winter s.:2/1, C+Ex [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Hrnčiřík Pavel doc. Ing. Ph.D.
Interchangeability : N445071
Examination dates   Schedule   
Annotation -
The course covers selected areas of artificial intelligence focusing primarily on different approaches to knowledge representation and reasoning both under certainty and uncertainty. In the practical part of the course the emphasis is mainly on rule-based programming in CLIPS and the design of fuzzy logic systems in Matlab.
Last update: Pátková Vlasta (20.04.2018)
Aim of the course -

Students will be able to:

Decide whether a given technical problem can be solved using fuzzy logic control.

Design an appropriate fuzzy logic controller for this problem. Propose optimization of its structure.

Select an appropriate knowledge representation paradigm for a given technical problem.

Design and implement rule-based systems in CLIPS.

Last update: Pátková Vlasta (20.04.2018)
Literature -

R: Giarratano J.C., Riley G.D.,Expert Systems: Principles and Programming,Course Technology,New York,2004,0534384471

R: Russell S.,Norvig P.,Artificial Intelligence: A Modern Approach,Prentice Hall, Englewood Cliffs,2002,0137903952

R: Ross J.T., Fuzzy Logic with Engineering Applications, Wiley-Blackwell, 2010, ISBN 978-0470743768

R: Passino K.M., Yurkovich S., Fuzzy Control, Addison-Wesley,New York, 1998,020118074X

R: Buckley J.J., Eslami E., An Introduction to Fuzzy Logic and Fuzzy Sets (Advances in Intelligent and Soft Computing), Physica, 2008, ISBN 978-3790814477

A: Zadeh L.A., Fuzzy Sets*, Information and Control 8, 338-353 (1965), http://www-bisc.cs.berkeley.edu/Zadeh-1965.pdf

Last update: Pátková Vlasta (20.04.2018)
Learning resources -

Other study aids:

Edward Sazonov: Fuzzy Logic and Applications, course EE509, Clarkson University, Potsdam, NY. http://www.intelligent-systems.info/classes/ee509/

Gary Riley: A Tool for Building Expert Systems. http://clipsrules.sourceforge.net/

Interactive MATLAB & Simulink Based Tutorials, http://www.mathworks.com/academia/student_center/tutorials/index.html?s_tid=acmain_lrn_tut

Last update: Pátková Vlasta (20.04.2018)
Requirements to the exam - Czech

Písemná zkouška

Last update: Mareš Jan (04.10.2023)
Syllabus -

1 Fuzzy logic. Mamdani inference method. Sugeno inference method.

2 Fuzzy controller design

3 Using the Matlab Fuzzy toolbox and Simulink for FC implementation

4 Individual project – fuzzy controller

5 Using Matlab toolboxes for optimization of FC presentation and outputs

6 Adaptive neuro-fuzzy inference system

7 Optimization of a fuzzy controller using machine learning

8 Knowledge representation: production systems

9 Development of expert systems using CLIPS

10 Knowledge representation – semantic networks, frames

11 Reasoning under uncertainty

12 Probabilistic approach for knowledge representation and reasoning

13 Individual project – knowledge-based system in CLIPS

14 Modern trends in artificial intelligence

Last update: Cejnar Pavel (04.09.2023)
Course completion requirements - Czech

Zápočet: Během semestru jsou na cvičeních zadávány samostatné úlohy, které je nutné vypracovat pro získání zápočtu. Dále je zadáván samostatný projekt, ze kterého je pro získání zápočtu nutné získat alespoň 50 % z max. možného bodového ohodnocení.

Zkouška: Zápočet předchází zkoušce, tj. bez získání zápočtu nelze zkoušku absolvovat. Vlastní zkouška má písemnou formu.

Last update: Hrnčiřík Pavel (08.02.2024)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 0.7 20
Práce na individuálním projektu 0.8 22
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 0.5 14
4 / 4 112 / 112
Coursework assessment
Form Significance
Regular attendance 20
Report from individual projects 30
Examination test 50

 
VŠCHT Praha