Faculty of Information Technology, BUT

Course details

Intelligent Systems

ISD Acad. year 2012/2013 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

Time span

26 hrs lectures, 26 hrs projects

Assessment points

60 exam, 40 projects

Department

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

  1. Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4700-1 
  2. Kecman, V.: Learning and Soft Computing, The MIT Press, 2001, ISBN 0-262-11255-8
  3. Munakata,T.: Fundamentals of the New Artificial Intelligence, Springer, 2008, ISBN 978-1-84628-838-8
  4. Rutkowski, L.: Flexible Neuro-Fuzzy Systems, Kluwer Academic Publishers, 2004, ISBN: 1-4020-8042-5
  5. Zaknih, A.: Neural Networks for Intelligent Signal Processing, World Scientific Publishing Co. Pte. Ltd., 2003, ISBN 981-238-305-0

Fundamental literature

  1. Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4700-1
  2. Cordón, O., Herrera, F., Hoffman, F., Magdalena, L.: Genetic Fuzzy systems, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4016-3
  3. Kecman, V.: Learning and Soft Computing, The MIT Press, 2001, ISBN 0-262-11255-8
  4. Munakata,T.: Fundamentals of the New Artificial Intelligence, Springer, 2008, ISBN 978-1-84628-838-8
  5. Rutkowski, L.: Flexible Neuro-Fuzzy Systems, Kluwer Academic Publishers, 2004, ISBN: 1-4020-8042-5
  6. Zaknih, A.: Neural Networks for Intelligent Signal Processing, World Scientific Publishing Co. Pte. Ltd., 2003, ISBN 981-238-305-0

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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