Prerequisites: solid mathematical skills. Particularly suitable for students of D-ITET, D-MAVT
This course discusses complex techno-socio-economic systems, their counter-intuitive behaviors, and how their theoretical understanding empowers us to solve some long-standing problems that are curently bothering the world.
Participants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop models for open problems, to analyze them, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to think scientifically about complex dynamical systems.
This course starts with a discussion of the typical and often counter-intuitive features of complex dynamical systems such as self-organization, emergence, (sudden) phase transitions at "tipping points", multi-stability, systemic instability, deterministic chaos, and turbulence. It then discusses phenomena in networked systems such as feedback, side and cascade effects, and the problem of radical uncertainty. The course progresses by demonstrating the relevance of these properties for understanding societal and, at times, global-scale problems such as traffic jams, crowd disasters, breakdowns of cooperation, crime, conflict, social unrests, political revolutions, bubbles and crashes in financial markets, epidemic spreading, and/or "tragedies of the commons" such as environmental exploitation, overfishing, or climate change. Based on this understanding, the course points to possible ways of mitigating techno-socio-economic-environmental problems, and what data science may contribute to their solution.
Voraussetzungen / Besonderes
Mathematical skills can be helpful
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Die Leistungskontrolle wird nur am Semesterende nach der Lerneinheit angeboten. Die Repetition ist nur nach erneuter Belegung möglich.
Zusatzinformation zum Prüfungsmodus
Students are expected to actively contribute to the lectures if there are sufficiently few participants to , each one will have to give a 10 minute presentation on a scientific paper selected together with the lecturer. These papers are typically about mathematical derivations and models related to the lecture. The quality of the presentation would be considered 50% in the final grading. In any case there is a 90 minute written exam, which typically takes place in the last lecture of the course. To pass the exam, at least 40% of the maximum number of points will have to be reached.