851-0101-86L Complex Social Systems: Modeling Agents, Learning, and Games
| Semester | Autumn Semester 2020 |
| Lecturers | N. Antulov-Fantulin, D. Helbing |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Comment | Number of participants limited to 100. Prerequisites: Basic programming skills, elementary probability and statistics. |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 851-0101-86 S | Complex Social Systems: Modeling Agents, Learning, and Games
 | 2 hrs |
| N. Antulov-Fantulin, D. Helbing |
Catalogue data
| Abstract | 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. |
| Learning objective | 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. |
| Content | 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. |
| Lecture notes | The lecture slides will be presented on the course web page after each lecture. |
| Literature | Agent-Based Modeling https://link.springer.com/chapter/10.1007/978-3-642-24004-1_2 Social Self-Organization https://www.springer.com/gp/book/9783642240034 Traffic and related self-driven many-particle systems Reviews of Modern Physics 73, 1067 https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.73.1067 An Analytical Theory of Traffic Flow (collection of papers) https://www.researchgate.net/publication/261629187 Pedestrian, Crowd, and Evacuation Dynamics https://www.research-collection.ethz.ch/handle/20.500.11850/45424 The hidden geometry of complex, network-driven contagion phenomena (relevant for modeling pandemic spread) https://science.sciencemag.org/content/342/6164/1337 Further literature will be recommended in the lectures. |
| Prerequisites / Notice | 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. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 3 credits |
| Examiners | N. Antulov-Fantulin, D. Helbing |
| Type | graded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
Learning materials
| Main link | http://www.vvz.ethz.ch/Vorlesungsverzeichnis/lerneinheit.view?semkez=2020W&ansicht=KATALOGDATEN&lern |
| Only public learning materials are listed. | |
Groups
| No information on groups available. |
Restrictions
| General |  : Special students and auditors need a special permission from the lecturers |
| Places | 100 at the most |
| Waiting list | until 19.10.2020 |
