Course details

Intelligent Systems

SIN Acad. year 2005/2006 Winter semester 5 credits

Current academic year

Introduction into intelligent systems theory, uncertain and incomplete information processing, intelligent systems design particularities, modeling and prototyping, intelligent control systems intelligent sensor systems, intelligent information systems, data mining, expert systems, distributed artificial intelligence, multiagent systems, robotic and multirobotic systems, biometric systems.

Guarantor

Janoušek Vladimír, doc. Ing., Ph.D. (DITS)

Language of instruction

Czech

Completion

Examination

Time span

  • 39 hrs lectures
  • 13 hrs projects

Department

Department of Intelligent Systems (UITS)

Subject specific learning outcomes and competences

Students acquire knowledge of principles of intelligent systems and so they will be able to design and construct such systems.

Learning objectives

To acquaint students with theory and principles of intelligent systems and with representative practical systems.

Prerequisite knowledge and skills

Artificial intelligence basics: Problem solving, state space search, problem decomposition, machine learning principles, statistical and structural pattern recognition. Fundamentals of computer vision. Base principles of natural language processing.

Study literature

    1. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
    2. Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557
    3. Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
    4. Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
    5. Automatizace. http://www.automatizace.cz/

Syllabus of lectures

  1. Introduction into intelligent systems theory, uncertain and incomplete information processing
  2. Intelligent systems design particularities, modeling and prototyping
  3. Intelligent control systems
  4. Intelligent sensor systems
  5. Intelligent (domestic) appliances 
  6. Intelligent building
  7. Intelligent transport systems
  8. Intelligent information systems
  9. Data mining
  10. Expert systems
  11. Distributed artificial intelligence, multiagent systems
  12. Robotic and multirobotic systems
  13. Biometric systems

Progress assessment

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Controlled instruction

  • Mid-term written test 
  • Individuální project

     

Back to top