Title:

Intelligent Systems

Code:SIN
Ac.Year:2005/2006
Term:Winter
Curriculums:
ProgrammeBranchYearDuty
IT-MSC-2MGM.1stCompulsory
IT-MSC-2MIN.1stCompulsory
IT-MSC-2MIS.1stCompulsory
IT-MSC-2MPS1stCompulsory
IT-MSC-2EITE1stCompulsory
Language:Czech, English
Public info:http://www.fit.vutbr.cz/study/courses/SIN/public/
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:3900013
 ExaminationTestsExercisesLaboratoriesOther
Points:50200030
Guarantee:Janoušek Vladimír, doc. Ing., Ph.D., DITS
Lecturer:Drahanský Martin, doc. Ing., Dipl.-Ing., Ph.D., DITS
Janoušek Vladimír, doc. Ing., Ph.D., DITS
Orság Filip, Ing., Ph.D., DITS
Zbořil František, doc. Ing., Ph.D., DITS
Zbořil František V., doc. Ing., CSc., DITS
Zendulka Jaroslav, doc. Ing., CSc., DIFS
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Substitute for:
Artificial Intelligence (UIN), DITS
 
Learning objectives:
To acquaint students with theory and principles of intelligent systems and with representative practical systems.
Description:
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.
Knowledge and skills required for the course:
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.
Learning outcomes and competences:
Students acquire knowledge of principles of intelligent systems and so they will be able to design and construct such systems.
Syllabus of lectures:
  1. Introduction
  2. Softcomputing
  3. Agent systems
  4. Machine learning
  5. Intelligent control systems
  6. Expert systems
  7. Planing
  8. Distributed AI
  9. Robotics
  10. Intelligent sensor systems
  11. Datamining, knowledge discovery
  12. Biometric systems
  13. Summary
Syllabus - others, projects and individual work of students:
Individual project - design of (part of) simple intelligent system
Fundamental literature:
  1. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
  2. Negnevitsky, M.: Artificial Intelligence, Addison Wesley, 2001, ISBN 0-321-20466-2
Study literature:
  1. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
  2. Negnevitsky, M.: Artificial Intelligence, Addison Wesley, 2001, ISBN 0-321-20466-2
Progress assessment:
  • Mid-term written test 
  • Individuální project