Course detail

Modelling and Simulation

FIT-MSDAcad. year: 2024/2025

Classification of systems and models. Different ways of describing models. Methodology of model construction, special types of models. Principles of implementation of simulation systems. Multiparadigmatic modeling and simulation. Parallel and distributed simulation. Real time simulation, interactive simulation.

The state examination topics:

  1. Theory of modeling and simulation, DEVS and its variants.
  2. Combined systems (continuous simulation and discrete events).
  3. Stochatic Petri nets.
  4. High-level petri nets.
  5. Interpreted Petri nets and control system modeling.
  6. Real-time simulation and interactive simulation.
  7. Anticipatory systems, nested and reflective simulations.
  8. Parallel and distributed simulation.
  9. Multisimulation, cloning of simulations, applications.
  10. Softcomputing and machine learning in systems modeling and simulation.

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

doc. Ing. Vladimír Janoušek, Ph.D.

Department

Department of Intelligent Systems (UITS)

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

Short tests in lectures, state of essay elaboration.
Lectures and essay elaboration.

Aims

Students will be introduced to design and implementation principles of simulation systems. Further, the techniques for modelling and simulation of various types of models will be presented. Special attention is paid to advanced simulation techniques including artificial intelligence.

The basics of modelling and simulation theory. Understanding the principles of simulation system implementation. Knowledge of advanced simulation techniques.
Ability to create system models and use simulation to solve problems.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

David R., Alla H,: Discrete, Continuos and Hybrid Petri Nets, Springer Verlag, 2010
Didier H. Besset: Object-Oriented Implementation of Numerical Methods: An Introduction with Java & Smalltalk, Morgan Kaufmann, 2000
Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
Janoušek, V.: Simulace a návrh vyvíjejících se systémů. Brno, CZ: Fakulta informačních technologií VUT v Brně, 2009.
Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
Ross S.: Simulation, Academic Press, 2002
Sarjoughian H., Cellier F.: Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies. Springer-Verlag New York Inc. 2001. ISBN: 0387950656
Zeigler B., Kim T., Praehofer H.: Theory of Modeling and Simulation. Academic Press Inc.,U.S.; 2nd Edition edition. 2000. ISBN: 0127784551

Classification of course in study plans

  • Programme DIT Doctoral 0 year of study, winter semester, compulsory-optional
  • Programme DIT Doctoral 0 year of study, winter semester, compulsory-optional
  • Programme DIT-EN Doctoral 0 year of study, winter semester, compulsory-optional
  • Programme DIT-EN Doctoral 0 year of study, winter semester, compulsory-optional

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, winter semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, winter semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, winter semester, elective

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Classes of problems solvable by simulation methods. Theory of dynamical systems.
  2. DEVS formalism and its variants.
  3. Architectures of simulation systems, principles of implementation.
  4. Examples of paradigm combinations - processes, Petri nets, DEVS and continuous systems.
  5. Interpreted Petri nets. Control systems modeling.
  6. Systems development based on modeling and simulation, real-time simulation, hardware-in-the-loop, human-in-the-loop, continuity model.
  7. Object-oriented and component approaches to modeling and simulation.
  8. Parallel and distributed simulation.
  9. Anticipatory systems. Nested simulation. Reflective simulation. 
  10. Multisimulations, cloning, independent time axes.
  11. Optimization, adaptation, learning.
  12. Modeling and simulation of intelligent systems. Softcomputing and simulation.
  13. Multiagent simulations. Complex systems simulation.

Guided consultation in combined form of studies

26 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.