Simulation of Dynamic Systems


InstructorProf. Dr. Daniel Fürstenau, Matthias Schulte-Althoff
SemesterWinter term 2019/20
Scope of Course
Credit Points6 ECTS
RoomGarystr. 21, 14195 Berlin Room 108a
StartOct 18, 2019 | 12:00 PM

Student Profile

Master students, primarily in Information Systems


There are no direct admission requirements. The course is recommended from the 1st semester in the Master's programme. 

 For project work, basic programming knowledge is advantageous, but not absolutely necessary, since the course is taught in small groups of 2 to 3 participants, in which different skills are required.


The simulation of dynamic systems as a tool for the description and analysis of complex systems is becoming more and more important in various practical and scientific areas: efficient design of processes in transport, production and hospitals, diffusion of information and innovations in marketing, sales, health care, etc.; economically efficient design of prices and services in the context of digital platforms and markets; analysis of risks in networked systems as well as in security-critical IT and communication infrastructures. These examples show the manifold application possibilities and questions for simulation.

The purpose of this seminar is to get to know the complete life cycle of a simulation study from conception, implementation, validation, experimentation and analysis and to apply it exemplarily. Simulation is the modelling of a real system, whereby knowledge about the real system is to be gained by targeted experiments on the model. 

The seminar focuses in particular on agent-based simulation, which is suitable for simulating complex adaptive systems such as financial markets or transport markets, and discrete event-based simulation, which can be used to investigate business process scenarios and queues. In addition, the seminar emphasizes the combination possibilities of simulation with machine learning techniques, which are becoming increasingly important.

The seminar is designed for 8 to max. 12 participants. Due to the small group size an intensive working atmosphere should be guaranteed. The seminar is concluded by a written elaboration of 10-12 pages, which documents the results of a practical project task. In the practical application, a well-known simulation tool (e.g. AnyLogic) is used.

Topics (excerpt)

- Simulation: basic types and distinction from optimization

- Agent based simulation

• Basics and methodical approach within the framework of modelling

• Parameterization and probability distributions

• Validation and analysis of agent-based simulation models 

• Experimentation and quantitative evaluations

• Case study: pricing in a transport market

- Discrete event-based simulation

• Basics and methodical approach within the framework of modelling

• Case study: capacity optimization in hospitals

- Simulation and machine learning

• Machine learning and big data analytics in the simulation process

• Further combination possibilities

• Case Study: Reinforcement Learning


LAW AM (2013) Simulation Modeling and Analysis (5th edition). McGraw Hill, New York.

WILENSKY U and RAND W (2015) An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT press, Boston, MA.

SHOHAM Y and LEYTON-BROWN (2008) Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge Univ. Press. Cambridge, UK.

TOLK A (2015) The Next Generation of Modeling & Simulation: Integrating Big Data and Deep Learning. Proceedings of the Conference on Summer Computer Simulation. San Diego, CA.


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Department Wirtschaftsinformatik