Dino Carpentras: Catalogue data in Autumn Semester 2023 |
| Name | Dr. Dino Carpentras |
| Address | Computational Social Science ETH Zürich, STD F 2 Stampfenbachstrasse 48 8092 Zürich SWITZERLAND |
| dino.carpentras@gess.ethz.ch | |
| Department | Humanities, Social and Political Sciences |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0101-86L | Complex Social Systems: Modeling Agents, Learning, and Games   Prerequisites: Basic programming skills, elementary probability and statistics. | 3 credits | 2S | D. N. Dailisan, D. Carpentras, D. Helbing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces mathematical and computational models to study techno-socioeconomic 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 to communicate their results through a project report and a short oral presentation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | See your own field of study in a wider context (“Science in Perspective”), e.g. see the psychological, social, economic, environmental, historical, ethical,or philosophical connections and implications. Learn to think critically and out of the box. Question what you believe you know for sure. Get to know surprising, counterintuitive properties of complex (non-linearly interacting, networked, multi-component) systems. Learn about collaboration. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | By the end of the course, the students should be able to better understand the literature on complex social systems, develop their own models for studying specific phenomena and report results according to the standards of the relevant scientific literature by presenting their results both numerically and graphically. At the end of the course, the students will deliver a report, computer code and a short oral presentation. To collect credit points, students will have to actively contribute and give a circa 30 minutes presentation in the course on a subject agreed with the lecturers, after which the presentation will be discussed. The presentation will be graded. Students are expected to implement themselves models of techno-socio-economic processes and systems, particularly agent-based models, complex networks models, decision making, group dynamics, human crowds, or game-theoretical models. Credit points are finally earned for the implementation of a mathematical or empirical model from the complexity science literature, its presentation, and documentation by a project report. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The lecture slides will be presented on the course Moodle 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 860-0011-00L | Complex Social Systems: Modeling Agents, Learning, and Games - With Coding Project Prerequisites: Good mathematical skills, basic programming skills, elementary probability and statistics. | 6 credits | 2S + 2A | D. N. Dailisan, D. Helbing, D. Carpentras | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. 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. 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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