Subject description - AE3B33KUI

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AE3B33KUI Cybernetics and Artificial Intelligence Extent of teaching:2+2c
Guarantors:  Roles:P,V Language of
teaching:
EN
Teachers:  Completion:Z,ZK
Responsible Department:13133 Credits:5 Semester:L

Anotation:

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.

Study targets:

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.

Course outlines:

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)

Exercises outline:

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

Literature:

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

Requirements:

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

Webpage:

http://cw.felk.cvut.cz/doku.php/courses/ae3b33kui/start

Keywords:

Cybernetics, artificial intelligence

Subject is included into these academic programs:

Program Branch Role Recommended semester
BEKME1 Communication Technology V 4
BEKME5 Komunikace a elektronika V 4
BEKME_BO Common courses V 4
BEKME4 Network and Information Technology V 4
BEKME3 Applied Electronics V 4
BEKME2 Multimedia Technology V 4
BEKYR1 Robotics P 2
BEKYR_BO Common courses P 2
BEKYR3 Systems and Control P 2
BEKYR2 Sensors and Instrumentation P 2
BEEEM1 Applied Electrical Engineering V 4
BEEEM_BO Common courses V 4
BEEEM2 Electrical Engineering and Management V 4
BEOI1 Computer Systems V 4
BEOI_BO Common courses V 4
BEOI3 Software Systems V 4
BEOI2 Computer and Information Science V 4


Page updated 17.6.2019 14:52:47, semester: Z,L/2020-1, L/2018-9, Z,L/2019-20, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)