SubjectsSubjects(version: 821)
Course, academic year 2017/2018
Artificial Intelligence - N445030
English title: Umělá inteligence
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2014
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: 30 / unknown (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
For type:  
Guarantor: Hrnčiřík Pavel Ing. Ph.D.
Annotation -
Last update: Hrnčiřík Pavel Ing. Ph.D. (11.08.2013)

The course provides basic overview of artificial intelligence covering number of different areas from problem solving by searching in state space to fuzzy logic. In the practical part of the course the emphasis is mainly on logical programming in Prolog and the design of simple fuzzy logic systems in Matlab.
Aim of the course -
Last update: Hrnčiřík Pavel Ing. Ph.D. (11.08.2013)

Students will be able to:

Know the basics of artificial intelligence.

Write simple programs in Prolog.

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

Design a simple fuzzy logic controller for this problem.

Literature -
Last update: Hrnčiřík Pavel Ing. Ph.D. (11.08.2013)

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: 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),

Learning resources -
Last update: Hrnčiřík Pavel Ing. Ph.D. (11.08.2013)

Other study aids:

Artificial Intelligence: A Modern Approach

Edward Sazonov: Fuzzy Logic and Applications, course EE509, Clarkson University, Potsdam, NY.

SWI-Prolog's home

Interactive MATLAB & Simulink Based Tutorials,

Requirements to the exam - Czech
Last update: Hrnčiřík Pavel Ing. Ph.D. (12.09.2011)

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: Hrnčiřík Pavel Ing. Ph.D. (24.09.2009)

1. Artificial Intelligence - definition, clasification, basic concepts

2. Problem solving - uninformed strategies

3. Problem solving - informed strategies, heuristic search

4. Two person games: min-max method, alpha-beta pruning

5. Knowledge representation - production systems

6. Knowledge representation - semantic networks, frames

7. Knowledge representation - first-order logic

8. Fuzzy systems, fuzzy sets

9. Fuzzy relation, model of semantic

10. Linguistic operators

11. Inference rules

12. Fuzzy controller

13. Prolog

14. Prolog

Registration requirements -
Last update: Hrnčiřík Pavel Ing. Ph.D. (11.08.2013)

Matematika I, Algoritmizace a programování

Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 1 28
5 / 5 140 / 140
Evaluation of a student
Form Balance
Aktivní účast na výuce 20
Protokoly z individuálních projektů 30
Zkouškový test 50