Title:

Modelling and Simulation

Code:MSD
Ac.Year:2010/2011 (Not opened)
Term:Winter
Curriculums:
ProgrammeBranchYearDuty
CSE-PHD-4DVI4-Elective
IT-PHD-3DIT3-Elective
Language:Czech
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:390090
 ExaminationTestsExercisesLaboratoriesOther
Points:00000
Guarantee:Zbořil František V., doc. Ing., CSc., DITS
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
 
Learning objectives:
  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.
Description:
  Simulation systems and their classification. Design and implementation of simulation systems. Special types of models. Multimodeling, multisimulation. Parallel and distributed simulation. Knowledge-based simulation, model optimization. Realtime and interactive simulation.
Subject specific learning outcomes and competences:
  The basics of modelling and simulation theory. Understanding the principles of simulation system implementation. Knowledge of advanced simulation techniques.
Generic learning outcomes and competences:
  Create, verify, and validate simulation models.
Syllabus of lectures:
 
  • Introduction. Types of problems, which can be solved using simulation methods. Dynamical systems theory.
  • Architectures of simulation systems and their classification. Principles of simulation system design and implementation.
  • Modeling and Simulation-Based Development of Systems. Hardware-in-the-loop, Human-in-the-loop, Model continuity.
  • Multimodels, multiparadigm modeling  and simulation, multiresolution modeling and simulation. Architectures of simulators.
  • Examples of multiparadigm modeling: Processes, FSA, Petri nets, DEVS.
  • Object-oriented and component approaches to modeling and simulation.
  • Parallel and distributed simulation.
  • Anticipatory systems. Nested simulation. Reflective simulation.
  • Architectures for multisimulations. Cloning, independent time axes.
  • Optimization, adaptation, learning.
  • Modeling and simulation of intelligent systems. Sftcomputing and simulation.
  • Architectures for multiagent simulations. Compex systems simulation.
  • Visualization. Interactive simulation.
Syllabus - others, projects and individual work of students:
 
  • Individual solution of specified simulation problem, or extending of given simulation system to allow the use of new modelling methods.
Fundamental literature:
 
  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Ross S.: Simulation, Academic Press, 2002
  • Zeigler B., Kim T., Praehofer H.: Theory of Modeling and Simulation. Academic Press Inc.,U.S.; 2nd Edition edition. 2000. ISBN: 0127784551
  • 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
Study literature:
 
  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Didier H. Besset: Object-Oriented Implementation of Numerical Methods: An Introduction with Java & Smalltalk, Morgan Kaufmann, 2000
  • Zeigler B., Kim T., Praehofer H.: Theory of Modeling and Simulation. Academic Press Inc.,U.S.; 2nd Edition edition. 2000. ISBN: 0127784551
  • 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