[Translation missing: page.coursepage.titleprefix] Simulation of complex systems

Much of modelling in the sciences focuses on simple models, highlighting key mechanisms using small sets of moving parts. However, in complex systems the interesting features are often a direct result of having large sets of particles or agents with different characteristics. This makes new tools a necessity. The course introduces simulation techniques frequently used in complex systems to handle models with many heterogeneous parts. The weight will be on agent-based modelling and networks. For each technique we discuss its background, where its strengths and weaknesses lie, and study examples in physics, biology and social science. We also learn how to validate the outcomes of simulation models in order to reach scientifically sound conclusions. Finally, we also learn how to evaluate the ethical implications of the simulations and of the choices made in the simulation models.

The course is based on a series of lectures covering the various topics. The students work on simulation projects in groups of two to four students. A tutor supervises each group. Complementary to the lectures there are supervised computer labs where the students solve a variety of small simulation tasks which should be reported as home assignments.

Handouts of shorter texts and articles related to the subjects discussed at the lectures.

The examination is based on:

- 40% homework assignments. Each homework is compulsory.
- 60% group project. This is also compulsory. The evaluation includes a oral presentation (20%) and a written report (40%).