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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2017/2018

Cybernetics and Artificial Intelligence

The course is not on the list Without time-table
Code Completion Credits Range Language
AE3B33KUI Z,ZK 5 2+2c
The course cannot be taken simultaneously with:
Cybernetics and Artificial Intelligence (A3B33KUI)
Cybernetics and Artificial Intelligence (BE5B33KUI)
Cybernetics and Artificial Intelligence (B3B33KUI)
The course is a substitute for:
Cybernetics and Artificial Intelligence (A3B33KUI)
Lecturer:
Tutor:
Supervisor:
Department of Cybernetics
Synopsis:

The course will enable students to understand the basic concepts, goals and methods of cybernetics and artificial intelligence, and align some individual topics studied in the bachelor stage into the more profound context of the study program. The syllabus contains topics concerned with general aspects of systems and information theory, problem solving and state space search principles, elements of game theory, knowledge and expert systems, elements of decision theory, recognition and machine learning. The most important feature of the course is its unifying conceptual approach to many, at first sight diverse, components of cybernetics and aritifical intelligence.

Requirements:

https://cw.felk.cvut.cz/doku.php/courses/a3b33kui/start

Syllabus of lectures:

Introduction to cybernetics, systems and models

Elements of general systems theory

Information, entropy, information transmission, coding - a cybernetic view

Algorithmic entropy, decidability

Problem solving, the resolution principle

Search algorithms, stochastic search

Game theory, two-player games

Knowledge representation, semantic networks, production systems, frames and scenarios

Expert systems, their architecture, uncertain information processing models

Decision and classification principles, Bayesian decision making, attributes, attribute space, recognition, cluster analysis

Structural recognition, relations to machine perception and image/scene analysis

Neural networks and their training, genetic and evolutionary algorithms

Machine learning

Applications (if timetable allows)

Syllabus of tutorials:

1. - 2. Cybernetic systems lab showcase

2. - 4. Seminar: Probability and entropy

3. - 4. Computer lab: System models

5. - 6. Seminar: Information transmission

5. - 6. Computer lab: Compression algorithms

6. - 10. Seminar: Search

7. - 10. Computer lab: Search

8. - 12. Seminar: Decision making, classification, recognition

9. - 12. Computer lab: Expert systems

10. - 13. Seminar with computer simulation: Evolutionary algorithms, neural networks

11. - 14. Machine learning, class credits

Study Objective:

The course will enable students to understand the basic

concepts, goals and methods of cybernetics and artificial

intelligence, and align some individual topics studied in

the bachelor stage into the more profound context of the

study program.

Study materials:

Nilsson, N. N.: Artificial Intelligence: A New Synthesis. Morgan Kaufmann Publ. San Francisco, 1998

Note:
Further information:
http://cw.felk.cvut.cz/doku.php/courses/ae3b33kui/start
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2017-11-23
For updated information see http://bilakniha.cvut.cz/en/predmet12813504.html