Lecturer(s)
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Course content
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Content of lectures: 1. Introduction to the issue, the definition of systems, basic concepts of simulation, simulation methods (development in time, scheduling of events) 2. Basic principles of systems thinking and modeling, describing behavior patterns, continuous and discrete systems, experiments 3. Cellular automata, the history, principles and actual state, the game of life 4. Event-driven models, Rule-based systems 5. System dynamics models based on the description of systems on a global level through the time development of internal resources, determined by their allowable flows and causal relationships 6. Description of system dynamics with the equations, the use of differential equations, the equilibrium state 7. Multi-agent models based on a botton-up creation model based on the behavior of individual elements (agents) and their interactions 8. Network modeling focused on simulating the behavior of entities within the environment and in particular their communication links 9. State models based on passive entities that pass through the allowed changes and continuously consume system resources 10. Combining simulation techniques to design more effective models 11. Experimental design, sensitivity analysis 12. Application of simulation techniques on selected issues of science and research and corporate practice, according to students preferences and interests
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Demonstration, Laboratory, Practical training, Case studies
- Semestral paper
- 26 hours per semester
- Class attendance
- 56 hours per semester
- Preparation for classes
- 48 hours per semester
- Preparation for exam
- 26 hours per semester
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Learning outcomes
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The course aims to teach students systems thinking which is necessary for the design of simulation models of complex systems. The selected simulation techniques applicable in solving business and research problems and decision support will be presented in lectures and practical seminars. The seminars will be based on case studies focused on individual techniques procedures which will be tested on selected software tools (such as AnyLogic) with a maximum application of the team approach.
Upon successful completion students will be able to: - orientate in the area of modeling and simulation systems, and know the techniques and methods of models design - use systems thinking for systems analysis - create models of simple systems - use software tools for simulation support - carry out simulation experiments - cooperate in teams on various positions
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Prerequisites
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It is advisable to have basic knowledge in the field of university mathematics and statistics and programming basics (this is not necessary).
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Assessment methods and criteria
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Written examination, Analysis of student's work activities (technical works), Analysis of creative work (musical, visual, literary), Test, Seminar work
During the semester, students work on projects arising from the subject matter. The exam is evaluated on the basis of semester, semestral work and theoretical test. Terms of endings: Compleeting exercise projects (about 5 tasks) - 5 x 10 p. (min. 25 p.) Semestral work - 40 b. (min. 20 b.) Test - 30 p. (min. 15 p.)
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Recommended literature
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Informační zdroje na síti Internet. Vzhledem k častým obměnám budou konkrétní místa upřesněna při zahájení výuky předmětu..
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Kirkwood C. W. System Dynamics Methods: A Quick Introduction - http://www.public.asu.edu/~kirkwood/sysdyn/SDIntro/SDIntro.htm.
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Pidd M.: Tools for Thinking: Modelling in Management Science - online.
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Russell S., Norvig P.:Artificial Intelligence: A Modern Approach, ISBN: 0-13-604259-7.
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Anylogic. AnyLogic website.
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Harvey Gould:. Introduction to Computer Simulation Methods, 2006, ISBN: 0-8053-7758-1.
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Jelínek, J. Webové stránky předmětu v systému Moodle.
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Law A.M. (2007) Simulation modeling and analysis. 4th edition. McGraw-Hill.
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