The spring semester 2021 will take place online until further notice. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers.

Dirk Helbing: Catalogue data in Autumn Semester 2016

Name Prof. Dr. Dirk Helbing
FieldComputational Social Science
Address
Computational Social Science
ETH Zürich, STD F 3
Stampfenbachstrasse 48
8092 Zürich
SWITZERLAND
Telephone+41 44 632 88 80
Fax+41 44 632 17 67
E-maildirk.helbing@gess.ethz.ch
DepartmentHumanities, Social and Political Sciences
RelationshipFull Professor

NumberTitleECTSHoursLecturers
851-0252-04LBehavioral Studies Colloquium Information 2 credits2KE. Stern, H.‑D. Daniel, D. Helbing, C. Hölscher, B. Rütsche, R. Schubert, C. Stadtfeld
AbstractThis colloquium offers an opportunity for students to discuss their ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It also offers an opportunity for students from other disciplines to discuss their research ideas in relation to behavioral science. The colloquium also features invited research talks.
ObjectiveStudents know and can apply autonomously up-to-date investigation methods and techniques in the behavioral sciences. They achieve the ability to develop their own ideas in the field and to communicate their ideas in oral presentations and in written papers. The credits will be obtained by a written report of approximately 10 pages.
ContentThis colloquium offers an opportunity for students to discuss their ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It also offers an opportunity for students from other disciplines to discuss their ideas in so far as they have some relation to behavioral science. The possible research areas are wide and may include theoretical as well as empirical approaches in Social Psychology and Research on Higher Education, Sociology, Modeling and Simulation in Sociology, Decision Theory and Behavioral Game Theory, Economics, Research on Learning and Instruction, Cognitive Psychology and Cognitive Science. Ideally the students (from Bachelor, Master, Ph.D. and Post-Doc programs) have started to start work on their thesis or on any other term paper.
Course credit can be obtained either based on a talk in the colloquium plus a written essay, or by writing an essay about a topic related to one of the other talks in the course. Students interested in giving a talk should contact the course organizers (Rütsche, Stern) before the first session of the semester. Priority will be given to advanced / doctoral students for oral presentations. The course credits will be obtained by a written report of approximately 10 pages. The colloquium also serves as a venue for invited talks by researchers from other universities and institutions related to behavioral and social sciences.
851-0585-04LLecture with Computer Exercises: Modelling and Simulating Social Systems with MATLAB Restricted registration - show details
Number of participants limited to 70.

Particularly suitable for students of D-MAVT, D-INFK, D-ITET, D-MTEC, D-PHYS.
3 credits2SD. Helbing, L. Sanders, O. Woolley
AbstractThis course introduces the mathematical software package MATLAB.

Students should learn to implement models of various social processes
and systems, and document their skills by a seminar thesis, as well as giving a short oral presentation.
ObjectiveThe students should learn how to use MATLAB as a tool to solve
various scientific problems. MATLAB is an integrated environment with a high level programming language which makes it possible to quickly find numerical solutions to a wide range of scientific problems. Furthermore, it includes a rich set of tools for graphically
presenting the results.

After the students have learned the basic structure of the programming language, they should be able to implement social simulation models in MATLAB and document their skills by a seminar thesis and finally give a short oral presentation.
ContentThis course introduces first the basic functionalities and features of the mathematical software package MATLAB, such as the simple operations with matrices and vectors, differential equations, statistical tools, the graphical representation of data in various forms, and video animations of spatio-temporal data. With this knowledge, students are expected to implement themselves in MATLAB, models of various social processes and systems, including agent-based models, e.g. models of interactive decision making, group dynamics, human crowds, or game-theoretical models.

Part of this course will consist of supervised programming exercises in a computer pool. Credit points are finally earned for the implementation of a mathematical model from the sociological literature in MATLAB and the documentation in a seminar thesis.
Lecture notesThe lecture slides will be presented on the course web page after each lecture.
Literature[1] MATLAB Primer, Seventh Edition, Timothy A. Davis and Kermit Sigmon, (Chapman & Hall, 2004).
[2] MATLAB kompakt, Wolfgang Schweizer, (Oldenbourg, 2006)

Further literature, in particular regarding computer models in the
social sciences, will be provided in the course.
Prerequisites / NoticeThe number of participants is limited to the size of the available computer teaching room. The MATLAB code related to the seminar thesis should be well enough documented for further use by others and must be handed over to the Chair of Sociology, in particular of Modeling and Simulation, for further free and unrestricted use.
851-0585-15LComplexity and Global Systems Science Information
Prerequisites: solid mathematical skills.
Particularly suitable for students of D-ITET, D-MAVT
3 credits2VD. Helbing, N. Antulov-Fantulin
AbstractThis 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.
ObjectiveParticipants 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.
ContentThis 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.
Prerequisites / NoticeMathematical skills can be helpful
851-0585-41LComputational Social Science Information Restricted registration - show details 3 credits2SD. Helbing, M. Leiss, O. C. Rouly
AbstractThe seminar aims at three-fold integration: (1) bringing modeling and computer simulation of techno-socio-economic processes and phenomena together with related empirical, experimental, and data-driven work, (2) combining perspectives of different scientific disciplines (e.g. sociology, computer science, physics, complexity science, engineering), (3) bridging between fundamental and applied work.
ObjectiveParticipants of the seminar should understand how tightly connected systems lead to networked risks, and why this can imply systems we do not understand and cannot control well, thereby causing systemic risks and extreme events.

They should also be able to explain how systemic instabilities can be understood by changing the perspective from a component-oriented to an interaction- and network-oriented view, and what fundamental implications this has for the proper design and management of complex dynamical systems.

Computational Social Science and Global Systems Science serve to better understand the emerging digital society with its close co-evolution of information and communication technology (ICT) and society. They make current theories of crises and disasters applicable to the solution of global-scale problems, taking a data-based approach that builds on a serious collaboration between the natural, engineering, and social sciences, i.e. an interdisciplinary integration of knowledge.
860-0011-00LModelling and Simulating Social Systems with MATLAB (with Coding Project) Information Restricted registration - show details
Only for MSc Science, Technology, and Policy.
6 credits2S + 2AD. Helbing, O. Woolley, L. Sanders
AbstractThis course introduces the mathematical software package MATLAB.

Students should learn to implement models of various social processes
and systems, and document their skills by a seminar thesis, a short oral presentation as well as a coding project.
ObjectiveThe students should learn how to use MATLAB as a tool to solve
various scientific problems. MATLAB is an integrated environment with a high level programming language which makes it possible to quickly find numerical solutions to a wide range of scientific problems. Furthermore, it includes a rich set of tools for graphically
presenting the results.

After the students have learned the basic structure of the programming language, they should be able to implement social simulation models in MATLAB and document their skills by a seminar thesis, a coding project and finally give a short oral presentation.