851-0101-86L  Complex Social Systems: Modeling Agents, Learning, and Games

Courses

Number	Title	Hours		Lecturers
851-0101-86 S	Complex Social Systems: Modeling Agents, Learning, and Games	2 hrs	Mon 16:15-18:00 ML H 44 »	D. N. Dailisan, D. Carpentras, D. Helbing

Catalogue data

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	Subject-specific Competencies Concepts and Theories assessed Techniques and Technologies assessed Method-specific Competencies Analytical Competencies assessed Decision-making assessed Media and Digital Technologies fostered Problem-solving assessed Project Management assessed Social Competencies Communication assessed Cooperation and Teamwork assessed Customer Orientation fostered Leadership and Responsibility assessed Self-presentation and Social Influence assessed Sensitivity to Diversity assessed Negotiation fostered Personal Competencies Adaptability and Flexibility assessed Creative Thinking assessed Critical Thinking assessed Integrity and Work Ethics assessed Self-awareness and Self-reflection assessed Self-direction and Self-management assessed

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits	3 credits
Examiners	D. Helbing, D. Carpentras, D. N. Dailisan
Type	graded semester performance
Language of examination	English
Repetition	Repetition only possible after re-enrolling for the course unit.

Learning materials

Groups

Restrictions

General	: Special students and auditors need a special permission from the lecturers
Places	Limited number of places. Special selection procedure.
Waiting list	until 08.10.2024

Offered in

Programme	Section	Type
Doctorate Humanities, Social and Political Sciences	Subject Specialisation	W
Science, Technology, and Policy Master	Electives	W
Science in Perspective	Sociology	W
Science in Perspective	D-INFK	W
Science in Perspective	D-ITET	W
Science in Perspective	D-PHYS	W