SubjectsSubjects(version: 855)
Course, academic year 2019/2020
  
Applied Artificial Intelligence - M445014
Title: Aplikovaná umělá inteligence
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2019
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 [hours/week]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
For type: Master's (post-Bachelor)
Guarantor: Hrnčiřík Pavel doc. Ing. Ph.D.
Interchangeability : N445071
Annotation -
Last update: Pátková Vlasta (20.04.2018)
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.
Aim of the course -
Last update: Pátková Vlasta (20.04.2018)

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.

Literature -
Last update: Pátková Vlasta (20.04.2018)

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

Learning resources -
Last update: Pátková Vlasta (20.04.2018)

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

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

Během semestru jsou zadávány 2 samostatné projekty, z kterých je pro získání zápočtu nutné získat alespoň 50 % z max. možného bodového ohodnocení. Vlastní zkouška má písemnou formu.

Syllabus -
Last update: Pátková Vlasta (20.04.2018)

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

2 Fuzzy controller. Using the Matlab Fuzzy toolbox and Simulink for FC implementation.

3 Individual project - fuzzy controller.

4 Adaptive neuro-fuzzy inference system.

5 Using the fuzzy approach in cluster analysis.

6 Knowledge representation: production systems.

7 Development of expert systems using CLIPS 1.

8 Development of expert systems using CLIPS 2.

9 Knowledge representation - semantic networks, frames.

10 Reasoning under uncertainty.

11 Probabilistic approach for knowledge representation and reasoning.

12 Individual project - knowledge-based system in CLIPS.

13 Individual project - knowledge-based system in CLIPS.

14 Modern trends in artificial intelligence.

Registration requirements -
Last update: Pátková Vlasta (20.04.2018)

Algorithms and Programming, Artificial Intelligence

Course completion requirements - Czech
Last update: Hrnčiřík Pavel doc. Ing. Ph.D. (24.04.2018)

Během semestru jsou zadávány 2 samostatné projekty, z kterých je pro získání zápočtu nutné získat alespoň 50 % z max. možného bodového ohodnocení. Vlastní zkouška má písemnou formu.

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

 
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