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Objectives and competences

- Depict the role of modeling and simulation in today's science at the complex systems analysis - Teach the students the methods and techniques of modeling and simulation in the sense of hybrid models - Determination of complex simulation models application in the form of dynamical simulators - Present the field of model application, effectiveness and facets at the support of business decisions - Study of the different methods of validation and verification of complex models and interpretation of results - Study of nonlinear systems in the field of organizational sciences

Content (Syllabus outline)

- Complex system simulation paradigm - Classification of mathematical and simulation models - Application fields of continuous, discrete event and agent-based models - Qualitative and quantitative modeling of continuous systems: directed graphs, system dynamics, nonlinear chaotic systems, sensitivity analysis - Discrete event simulation - Random generators and statistical distributions - Modeling with event graphs - Process oriented models - Modeling with Petri nets - Agent based models - Modeling of Cyber-physical systems - Hybrid models - Validation of models - Experimental design and result analysis

Learning and teaching methods

- lectures - seminar - tutorial

Intended learning outcomes - knowledge and understanding

Knowledge and understanding: • Ability to define the specific problem as the simulation model by the application of hybrid simulation techniques • Analysis of data and design of experiments • Knowledge and understanding of simulation tools and their application • Understanding of different simulation techniques and areas of application • Mastering of holistic development of systems for decision support based on the hybrid simulation techniques

Intended learning outcomes - transferable/key skills and other attributes

- Foster interdisciplinary collaboration between academia, research and industry experts at the problem solving with the methods of simulation - Mastering of holistic development of systems for decision support based on the hybrid simulation techniques

Readings

- Strogatz S. (2014) Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (Studies in Nonlinearity), Westview Press. - Sayama H (2015) Introduction to the Modeling and Analysis of Complex Systems, Open SUNY Textbooks - Miller J.H. (2016) A Crude Look at the Whole: The Science of Complex Systems in Business, Life, and Society, Basic Books - Mobus G.E. Kalton M.C. (2015) Principles of Systems Science (Understanding Complex Systems), Springer - Gros, C. (2009) Complex and Adaptive Dynamical Systems: A primer. Springer, New York. - Severance, F. L. (2001) System Modeling and Simulation: An Introduction, John Wiley & Sons, Chichester. - Zeigler, P. (2000) Theory of modeling and Simulation, Academic Press.

Prerequisits

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  • red. prof. dr. ANDREJ ŠKRABA, univ. dipl. org.

  • Seminar paper: 60
  • Coursework: 40

  • : 36
  • : 24
  • : 180

  • Slovenian
  • Slovenian

  • ORGANIZATION AND MANAGEMENT OF INFORMATION SYSTEMS - 2nd