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Dirk Helbing: Katalogdaten im Frühjahrssemester 2016

NameHerr Prof. Dr. Dirk Helbing
LehrgebietComputational Social Science
Adresse
Computational Social Science
ETH Zürich, STD F 3
Stampfenbachstrasse 48
8092 Zürich
SWITZERLAND
Telefon+41 44 632 88 80
Fax+41 44 632 17 67
E-Maildirk.helbing@gess.ethz.ch
DepartementGeistes-, Sozial- und Staatswissenschaften
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
364-1058-00LRisk Center Seminar Series Information Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 50
0 KP2SB. Stojadinovic, K. W. Axhausen, D. Basin, A. Bommier, L.‑E. Cederman, P. Embrechts, H. Gersbach, H. R. Heinimann, D. Helbing, H. J. Herrmann, W. Mimra, G. Sansavini, F. Schweitzer, D. Sornette, B. Sudret, U. A. Weidmann
KurzbeschreibungThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling and governing complex socio-economic systems, and managing risks and crises. Students and other guests are welcome.
LernzielParticipants 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 novel mathematical models and approaches for open problems, to analyze them with computers or other means, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level.
InhaltThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the seminar. Students and other guests are welcome.
SkriptThere is no script, but the sessions will be recorded and be made available. Transparencies of the presentations may be put on the course webpage.
LiteraturLiterature will be provided by the speakers in their respective presentations.
Voraussetzungen / BesonderesParticipants should have relatively good scientific, in particular mathematical skills and some experience of how scientific work is performed.
851-0252-04LBehavioral Studies Colloquium Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 50
2 KP2KC. Hölscher, H.‑D. Daniel, A. Diekmann, D. Helbing, V. Schinazi, R. Schubert, C. Stadtfeld, E. Stern
KurzbeschreibungThis 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.
LernzielStudents 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.
InhaltThis 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 (Schinazi, Hoelscher) 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.
851-0585-37LSocial Modelling, Agent-Based Simulation and Collective Intelligence Information
This course is thought be primarily for PhD students with quantitative skills and interests in modeling and computer simulations.
Particularly suitable for students of D-INFK, D-ITET, D-MAVT, D-MTEC, D-PHYS
3 KP2VD. Helbing, O. C. Rouly
KurzbeschreibungFormal models of societies greatly improved our understanding of social processes, the conditions under which they have negative outcomes, and the design of mechanisms that hamper unfavorable dynamics. In each course session, a societal problem (e.g. residential segregation, crowd disasters, economic bubbles) is discussed and students learn how to develop mechanisms that help prevent the problem.
LernzielThe course has three aims. First, students will be introduced to key formal models of social processes. Second, students learn how to analyze formal models in order to derive predictions about the conditions under which societal problems emerge. Third, students learn to use formal modeling to develop mechanisms that hamper problems. The course will consist of two parts. Part I introduces students to the most important formal models of social processes. Each session will focus on one particular societal problem, introducing existing models, their predictions about the conditions under which the problem emerges, and potential interventions. In Part II students will work on small projects, either developing and analyzing a new model or extending existing formal models.
851-0585-38LData Science in Techno-Socio-Economic Systems Belegung eingeschränkt - Details anzeigen
Number of participants limited to 70.

This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations.

Particularly suitable for students of D-INFK, D-ITET, D-MAVT, D-MTEC, D-PHYS
3 KP2VE. Pournaras, D. Helbing, I. Moise
KurzbeschreibungThis course introduces how techno-socio-economic systems in our nowadays digital society can be better understood with techniques and tools of data science. Students shall learn the fundamentals of data science, machine learning, but also advanced distributed real-time data analytics in the Planetary Nervous System. Students shall deliver and present a seminar thesis at the end of the course.
LernzielThe goal of this course is to qualify students with knowledge on data science as a way to understand complex techno-socio-economic systems in our nowadays digital societies. This course aims to make students capable of applying the most appropriate and effective techniques of data science under different application scenarios. The course aims to engage students in exciting state-of-the-art scientific and collaboration platforms such as the Planetary Nervous System. The course shall increase the awareness level of students about the challenges and open issues of data science in socio-technical domains such as privacy. Finally students have the opportunity to develop their writing, presentation and collaboration skills based on a seminar thesis they have to deliver and present at the end of the course
851-0585-40LControversies in Game Theory: In Honour of John F. Nash Information
This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations.
3 KP1VD. Helbing, H. Nax, H. Rauhut
KurzbeschreibungThe mini-course `Controversies in Game Theory II' consists of five course units that provide an in-depth introduction to issues in game theory motivated by the existence of social preferences and their implications for mechanism design. The course integrates theory from sociology, economics, physics, control theory, disaster response and biology.
LernzielStudents 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 of individual preferences and mechanism design.
851-0585-41LFrom Computational Social Science to Global Systems Science Information Belegung eingeschränkt - Details anzeigen 3 KP2SD. Helbing, M. Leiss, B. Pradelski
KurzbeschreibungThe specialized PhD 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 disciplines (e.g. sociology, computer science, physics, complexity science, engineering), 3)bridging between fundamental and applied work.
LernzielParticipants 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.