Andrea Musso: Catalogue data in Spring Semester 2024 |
| Name | Mr Andrea Musso |
| Address | Computational Social Science ETH Zürich, STD F 5 Stampfenbachstrasse 48 8092 Zürich SWITZERLAND |
| andrea.musso@gess.ethz.ch | |
| Department | Humanities, Social and Political Sciences |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 860-0022-00L | Complexity and Global Systems Science   Prerequisites: solid mathematical skills. Particularly suitable for students of D-ITET, D-MAVT and ISTP | 3 credits | 2S | D. Helbing, C. Carissimo, A. Musso | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | 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 currently bothering the world. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | 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 cascading 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | "Social Self-Organization Agent-Based Simulations and Experiments to Study Emergent Social Behavior" Helbing, Dirk ISBN 978-3-642-24004-1 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Philip Ball Why Society Is A Complex Matter https://www.springer.com/gp/book/9783642289996 Globally networked risks and how to respond Nature: https://www.nature.com/articles/nature12047 Global Systems Science and Policy https://library.oapen.org/bitstream/handle/20.500.12657/28004/1001993.pdf?sequence=1#page=214 Managing Complexity: Insights, Concepts, Applications https://www.springer.com/gp/book/9783540752608 Further links: http://global-systems-science.org http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS-06-06-2013-F1.pdf http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS_SynthesisPaper_070613_final.pdf Further literature will be recommended in the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Mathematical skills can be helpful. Students need to present a new subject, for which they have not earned any credit points before. Good scientific practices, in particular citation and quotation rules, must be properly complied with. Chatham House rules apply to this course. Materials may not be shared without previous written permission. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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