Course details

Artificial Intelligence

UIN Acad. year 2003/2004 Summer semester 6 credits

Current academic year

Problem solving, state space search, problem decomposition, games playing. Knowledge representation. AI languages (PROLOG, LISP). Machine learning principles. Statistical and structural pattern recognition. Fundamentals of computer vision. Basic principles of natural language processing. Basic principles of expert systems.

Details ...

Guarantor

Zbořil František, doc. Ing., CSc. (DITS)

Language of instruction

Czech

Completion

Examination

Time span

Department

Faculty of Information Technology (FIT)

Subject specific learning outcomes and competences

Students acquire knowledge of various approaches of problem solving and basic information about machine learning, computer vision, natural language processing and expert systems. They will be able to create programs using heuristics for problem solving.

Learning objectives

To give the students the knowledge of fundamentals of artificial intelligence, namely knowledge of problem solving approaches, machine learning principles and general theory of recognitions. Students acquire base information about computer vision, natural language processing and expert systems.

Study literature

  • Zbořil,F., Hanáček,P.: Umělá inteligence, Skripta VUT v Brně, VUT v Brně, 1990, ISBN 80-214-0349-7
  • Mařík,V., Štěpánková,O., Lažanský,J. a kol.: Umělá inteligence (1)+(2), ACADEMIA Praha, 1993 (1), 1997 (2), ISBN 80-200-0502-1

Fundamental literature

  • Russel,S., Norvig.,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2 
  • Luger,G.F., Stubblefield,W.A.: Artificial Intelligence, The Benjamin/Cummings Publishing Company, Inc., 1993, ISBN 0-8053-4785-2

Progress assessment

Written mid-term exam

Course inclusion in study plans

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