Course details
Modelling and Simulation
MSD Acad. year 2019/2020 Winter semester
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.
Guarantor
Language of instruction
Completion
Time span
- 39 hrs lectures
- 9 hrs pc labs
Assessment points
- 70 pts final exam (written part)
- 30 pts projects
Department
Lecturer
Instructor
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.
Create, verify, and validate simulation models.
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.
Study literature
- 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
- 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
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.
Course inclusion in study plans