Prerequisites: Basic programming skills, elementary probability and statistics.
This course introduces mathematical and computational models to study techno-socio-economic systems and the process of scientific research. Students develop a significant project to tackle techno-socio-economic challenges in application domains of complex systems. They are expected to implement a model and communicating their results through a seminar thesis and a short oral presentation.
The students are expected to know a programming language and environment (Python, Java or Matlab) as a tool to solve various scientific problems. The use of a high-level programming environment makes it possible to quickly find numerical solutions to a wide range of scientific problems. Students will learn to take advantage of a rich set of tools to present their results numerically and graphically.
The students should be able to implement simulation models and document their skills through a seminar thesis and finally give a short oral presentation.
Students are expected to implement themselves models of various social processes and systems, including agent-based models, complex networks models, decision making, group dynamics, human crowds, or game-theoretical models.
Part of this course will consist of supervised programming exercises. Credit points are finally earned for the implementation of a mathematical or empirical model from the complexity science literature and the documentation in a seminar thesis.
The lecture slides will be presented on the course web page after each lecture.
Literature, in particular regarding computer models in the (computational) social sciences, will be provided in the course.
Voraussetzungen / Besonderes
The number of participants is limited to the size of the available computer teaching room. The source code related to the seminar thesis should be well enough documented.
Good programming skills and a good understanding of probability & statistics and calculus are expected.
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)