From 2 November 2020, the autumn semester 2020 will take place online. Exceptions: Courses that can only be carried out with on-site presence.
Please note the information provided by the lecturers via e-mail.

Dirk Helbing: Catalogue data in Autumn Semester 2018

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 Colloquium2 credits2KU. Brandes, V. Amati, H.‑D. Daniel, D. Helbing, C. Hölscher, M. Kapur, R. Schubert, C. Stadtfeld, E. Stern
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 (Ziegler, Kapur) 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: Modeling and Simulating Social Systems in MATLAB (or Python)
Particularly suitable for students of D-MAVT, D-INFK, D-ITET, D-MTEC, D-PHYS.
3 credits2SD. Helbing, L. Aguilar Melgar, N. Antulov-Fantulin
AbstractThis course introduces mathematical and computational models to study social systems and the process of scientific research.

Students develop a significant project, implementing a model and communicating their results through a seminar thesis and a short oral presentation.
ObjectiveThe students should learn how to use a high level programming environment (MATLAB or Python) 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 learnt to take advantage of a rich set of tools to present their results numerically and graphically.

After the students have learned the basic structure of the programming language, they should be able to implement social simulation models and document their skills through a seminar thesis and finally give a short oral presentation.
ContentThis course introduces first the basic functionalities and features of the high level programming environments (MATLAB and Python), 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 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. Credit points are finally earned for the implementation of a mathematical model from the sociological literature and the documentation in a seminar thesis.
Lecture notesThe lecture slides will be presented on the course web page after each lecture.
LiteratureLiterature, 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 source 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 Computational Social Science (COSS) for further free and unrestricted use.
851-0585-41LComputational Social Science Restricted registration - show details
Number of participants limited to 50
3 credits2SD. Helbing, T. Guo
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.
851-0585-48LControversies in Game Theory: Collectives and Individuals
Number of participants limited to 80
3 credits2VD. Helbing, H. Nax, H. Rauhut
AbstractThe mini-course `Controversies in Game Theory' consists of 5 course units that provide an in-depth introduction to issues in game theory motivated by real-world issues related to the tensions that may result from interactions in groups, where individual and collective interests may conflict. The course integrates theory from various disciplines.
ObjectiveStudents are encouraged to think about human interactions, and in particular in the context of game theory, in a way that is traditionally not covered in introductory game theory courses. The aim of the course is to teach students the complex conditional interdependencies in group interactions.
Prerequisites / NoticeThis course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations.
851-0585-49LSelf-Organizing Multi-Agent Systems
Number of participants limited to 100.
3 credits2VD. Helbing, E. Pournaras
AbstractThis course introduces modeling and simulation techniques for multi-agent systems in the era of Internet of Things. Topics such as collective intelligence and decentralized combinatorial optimization are covered. Students will prototype autonomous self-organizing agents to tackle techno-socio-economic challenges in application domains of smart cities and beyond.
ObjectiveThe learning objectives of this course is to teach how to model, design and build self-organizing (multi-)agent systems in distributed techno-socio-economic systems such as smart grids, smart cities, pedestrian flows, traffic systems, and others. Students will be especially prepared to apply such systems in the era of Internet of Things, Big Data and distributed sharing economies. For this reason, students will experiment will real-world data as well as simulation and prototyping software with which they will examine and measure emergent phenomena such as traffic jams or power cascading failures. Τhe course stretches from simple, reactive agents to more sophisticated, decision-making or cognitive agents. The ultimate goal is to construct mechanims based on state of the art distributed optimization and machine learning techniques to improve collective and system-wide objectives related to reliability, resilience, sustainability, fairness and others.
860-0011-00LModeling and Simulating Social Systems in MATLAB (or Python) - With Coding Project Restricted registration - show details
Only for Science, Technology, and Policy MSc and MAS.
6 credits2S + 2AN. Antulov-Fantulin, D. Helbing, L. Aguilar Melgar
AbstractThis course introduces mathematical and computational models to study social systems and the process of scientific research.

Students develop a significant project, implementing a model and communicating their results through a seminar thesis and a short oral presentation.
ObjectiveThe students should learn how to use a high level programming environment (MATLAB or Python) 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 learnt to take advantage of a rich set of tools to present their results numerically and graphically.

After the students have learned the basic structure of the programming language, they should be able to implement social simulation models and document their skills through a seminar thesis and finally give a short oral presentation.
ContentThis course introduces first the basic functionalities and features of the high level programming environments (MATLAB and Python), 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 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. Credit points are finally earned for the implementation of a mathematical model from the sociological literature and the documentation in a seminar thesis.
Lecture notesThe lecture slides will be presented on the course web page after each lecture.
LiteratureLiterature, 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 source 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 Computational Social Science (COSS) for further free and unrestricted use.
860-0030-00LDigital Sustainability Restricted registration - show details
Number of participants limited to 45.

This LE is a replacement for LE 851-0591-00 Digital Sustainability in the Knowledge Society. Students who had been enrolled in LE 851-0591-00 are not allowed to enroll for 860-0030-00L and collect credit points.

Particulary suitable for students of D-INFK, D-ITET, D-MATL, D-MAVT, D-MTECT, D-USYS
3 credits2VM. M. Dapp, D. Helbing
AbstractHow do various interest groups influence the methods of production, distribution, and use of digital resources? Current models focusing on strong intellectual property rights are contrasted with open models like, e.g. Open Source/Content/Access. The course discusses consequences from different models and introduces »digital sustainability« as an alternative vision for society.
ObjectiveAt the heart of the discourse is the handling of digital goods and intellectual property in society. Digitization and the Internet allow handling knowledge in a way, which directly contrasts with the traditional understanding of "intellectual property" and the industries based on it. Starting from economic and legal basics, we compare proprietary and open/"free" models. Sustainable development as a concept is transferred to digital goods, taking into account the particular nature of digital stuff.
After the lecture, you should (hopefully) be able to
- characterize the nature of digital goods vs. physical goods
- critique the basic concepts of copyright and patent rights
- explain the basic principles of blockchains as the most recent open design
- explain the political/legal and economic differences between proprietary and open approaches to the production and use of digital goods
- using an example, explain the meaning of digital sustainability and argue why it is relevant for a knowledge society
- transfer the ideas of the free/open source software model to other digital goods (e.g., open content, open access)
ContentTechnical reality: Within minutes you can make perfect copies of high-value digital goods of knowledge or culture (as text, audio, video, image or software) and distribute them around the globe -- for free. «Digitization plus Internet» allows for the first time in humankind's history the (theoretically) free access and global exchange of knowledge at minimal cost. A tremendous opportunity for societal development, in north and south. «Cool, so what's the problem?»
The problem is, that this reality poses a fundamental threat to today's business model of the knowledge and culture industries (starting from the music label and Hollywood, via publishers, up to software vendors). Powerful commercial interests are at stake as «knowledge» (the fourth factor of production) will become ever more important in the 21st century. Accordingly, «piracy» and «file-sharing» are attacked with all means. At the core lies the question about the design of property in digital assets. For that, we apply a concept of «intellectual property», which is several hundred years old and does not address digtal reality in an adequate manner, sometimes leading to absurd situations. Its original goal seems to get forgotten: to help society develop by spreading knowledge as much as possible.
Using the PC becomes the new cultural technique of the 21st century. In contrast to «reading, writing and arithmetics», this new cultural technique cannot exist in isolation, but depends on a hard- and software infrastructure. This dependency extends to the provider of the infrastructure, who can define technical rules, which can take away or restrict the user's freedom. Even advanced users may have difficulties in recognizing these, often hidden, restrictions and in evaluating their societal relevance. But exactly these invisible consequences we need to understand and investigate, because they decide about access, distribution and usage of digital knowledge.
Comparable to the environmentalist movement of the 60s and 70s, a growing political movement for «Free Software» exists today, with «GNU/Linux» as its most popular symbol. The movement fights against treating software code as private property but as a central cultural good available to all without private interests. Based on the success of the Free Software movement, new initiatives extend the concepts to other domains (e.g. scientific knowledge, music)...
As a «teaser» to the lecture, you are invited to read the essay «ETH Zurich - A Pioneer in Digital Sustainability!». It can be downloaded from www.essays2030.ethz.ch.
Lecture notesSlides and other material (both usually in English) will be made available on a weekly basis as the lecture proceeds.
LiteratureContent of the following books is covered (PDFs freely available online):
1 Volker Grassmuck, Freie Software - Zwischen Privat- und Gemeineigentum, Bundeszentrale für Politische Bildung, 2. Aufl. Bonn 2004.
2 François Lévêque & Yann Ménière, The Economics of Patents and Copyright, Berkeley Electronic Press, 2004.
3 Yochai Benkler, The Wealth of Networks, Yale University Press. New Haven 2006.

Other recommended books are:
1 (general) Chris DiBona et al., Open Sources Voices from the Open Source Revolution, O'Reilly, 1999.
2 (pol. sc.) Steven Weber, The Success of Open Source, Harvard UP, 2004.
3 (law) James Boyle, Shamans, Software, & Spleens - Law and The Construction of the Information Society, Harvard UP, 1996.
4 (law) Lawrence Lessig, Code and Other Laws of Cyberspace, Basic Books, New York 1999.
Prerequisites / NoticeFor administrative and didactic reasons (high level of interaction and credit group assignments on current hot topics), the number of participants is limited to 45.
Of course, any interested person is invited to attend the lecture without doing the group assignment.