Faculty of Information Technology, BUT

Course details

Intelligent Systems

ISD Acad. year 2007/2008 Summer semester

Tolerance of imprecision and uncertainty as main attribute of ISY. Intelligent systems based on combinations of various theories - simulation, graphics, neural networks, fuzzy and rough sets and genetic algorithms: expert systems, intelligent information systems, machine translation systems, intelligent sensor systems, intelligent control systems, intelligent robotic systems.

Guarantor

Language of instruction

Czech

Completion

Examination (written+oral)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

100 exam

Department

Lecturer

Subject specific learning outcomes and competences

Students acquire knowledge of principles of intelligent systems and so they will be able to design these systems to solving of various practical problems.

Learning objectives

To give the students the knowledge of intelligent systems design (control, production, etc.) based on combinations of various theories: simulation, graphics, neural networks, fuzzy and rough sets and genetic algorithms.

Prerequisite kwnowledge and skills

Fundamental knowledge of artificial intelligence in a scope of Artificial Intelligence and Neural Network courses of current study program in FIT. 

Study literature

  • Russel,S., Norvig.,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2  

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  
  • Looney,C.G.: Pattern Recognition using neural networks, Theory and algorithms for Engineers and Scienntists, Oxford University Press, Inc., 1997, ISBN 0-19-507920-5
  • Dean,T., Allen,J., Yiannis,A.: Artificial Intelligence, Theory and Practice, The Benjamin/Cummings Publishing Company, Inc., 1995, ISBN 0-8053-2547-6

Syllabus of lectures

  1. Introduction, soft computing and ISY
  2. Expert systems
  3. Intelligent information systems
  4. Machine translation systems
  5. Surrounding environment perception, intelligent sensor systems
  6. Analysis of sensor date, environment model design
  7. Planning of the given task solution
  8. Control systems with neural networks
  9. Fuzzy control systems
  10. Neuro-fuzzy systems
  11. he use of rough sets and genetic algorithms in ISY
  12. Intelligent robotic systems
  13. Navigation of mobile robots

Syllabus - others, projects and individual work of students

  • Individual projects - designs of intelligent systems for solving some practical problem

Course inclusion in study plans

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