545-0492/01 – New Methods in System Practice (MNSP)

Goal is analysis of system dynamics problems and models synthesis. Student will be able to providing experiments with models for prediction and recommendation of solution problems.

anglicky česky německy In this course students will be familiar with the theoretical and practical knowledge in the field of systems thinking and system dynamics, such as system archetypes, nonlinearities, feedback, delay, mental models, causal loop diagrams, etc. Students will also be introduced to tools for the description and modeling dynamical systems. The course will explain how to create dynamic models. Through examples of modeling practices, students learn about the modeling tool Powersim. First System - definition view of the objects from the systemic perspective, depth and resolution of the system, the angle, open closed systems, types, elements, links, system, subsystem, internal variables, external variables, diagram of system boundaries Second Complexity and complexity - the complexity of the concept, detailed and dynamic complexity, interdependence, nonlinearity, uncertainty, feedback (positive, negative, additive, proportional feedback, the effects of delay), delay Third Systems thinking - mental models, systems thinking skills 4th System tools and creative thinking 5th System archetypes 6th System dynamics 7th To create models - problem definition, data collection, determine the assumptions and hypotheses, definitions of variables, their units and determine their types (levels, flows, constants, variables), formulation and formalization of the model, testing the model, what if analysis and simulation of the model etc. 8th Modeling of dynamic systems - definitions of variables, elements utilized in the model (flow, level, constants, variables, connections), and set the time step in the simulation, integration methods 9th Advanced modeling tools options - elements for entering the input values ​​of the model (graph functions, input fields, potentiometers, etc..), Components for displaying the results of simulations (graphs, value fields, tables, etc.), creation of a simulator 10th Advanced options modeling tools - Export and import values ​​for a file, using arrays 11th Modeling basic building blocks of mathematical models and their interpretation (sample transfer mathematical description - differential equations to model) - positive feedback, negative feedback, S curve 12th Modeling basic building blocks of models - overshoot and collapse, oscillations, simultaneous streams 13th Practical examples of models - limits to growth, population aging chain, tank, loan, bank account 14th Presentation software other means for modeling dynamics (Powersim, Vensim, Stella, IThing, Dynamo)

RUSSEL, S., NORVIG, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2, 932 pp

Homeworks, tests, projects.