Course detail

Intelligent Systems

FIT-SINAcad. year: 2009/2010

Intelligent system, intelligent systems modeling, simulation in the design of systems, uncertain and incomplete information processing, introduction to softcomputing, agent and multiagent architectures, learning and adaptive systems, reinforcement learning, planing and scheduling, applications.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Vladimír Janoušek, Ph.D.

Department

Department of Intelligent Systems (UITS)

Learning outcomes of the course unit

Students acquire knowledge of principles and design of intelligent systems.

Prerequisites

Artificial intelligence basics: Problem solving, state space search, problem decomposition.
Modeling and Simulation basics: System, model, simulation, simulation time, discrete event simulation, continuous systems simulation.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

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

Course curriculum

  1. Introduction. Intelligent systems overview
  2. Agent architectures
  3. Simulation modeling in the development of intelligent systems
  4. Fuzzy logic and fuzzy control
  5. Learning systems. Neural networks
  6. Genetic algorithms. Genetic programming
  7. Markov decision process, reinforcement learning
  8. Planing and Scheduling 
  9. Games theory
  10. Robotic systems
  11. Multiagent systems
  12. Selected applications
  13. Summary

Work placements

Not applicable.

Aims

To acquaint students with theory and principles of intelligent systems.

Specification of controlled education, way of implementation and compensation for absences

  • Mid-term written test
  • PC lab
  • Individuální project

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

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

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBI , 1 year of study, winter semester, compulsory-optional
    branch MBS , 0 year of study, winter semester, elective
    branch MGM , 0 year of study, winter semester, compulsory-optional
    branch MGM , 1 year of study, winter semester, compulsory
    branch MIN , 2 year of study, winter semester, compulsory
    branch MIN , 1 year of study, winter semester, compulsory
    branch MIS , 0 year of study, winter semester, compulsory-optional
    branch MIS , 1 year of study, winter semester, compulsory
    branch MMI , 0 year of study, winter semester, elective
    branch MMM , 0 year of study, winter semester, elective
    branch MPS , 1 year of study, winter semester, compulsory
    branch MPV , 1 year of study, winter semester, compulsory-optional
    branch MSK , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Introduction. Intelligent systems overview
  2. Agent architectures
  3. Simulation modeling in the development of intelligent systems
  4. Fuzzy logic and fuzzy control
  5. Learning systems. Neural networks
  6. Genetic algorithms. Genetic programming
  7. Markov decision process, reinforcement learning
  8. Planing and Scheduling 
  9. Games theory
  10. Robotic systems
  11. Multiagent systems
  12. Selected applications
  13. Summary

Fundamentals seminar

10 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Jazyky pro umělou inteligenci
  2. Základy Smalltalku
  3. Modelování na bázi DEVS
  4. Modelování inteligentních systémů
  5. Simulovaná robotika

Exercise in computer lab

2 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Project

13 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.