Heinrich Nax: Catalogue data in Autumn Semester 2019
|Name||PD Dr. Heinrich Nax|
|Field||Game theory and computational/experimental social sciences|
Computational Social Science
ETH Zürich, CLD C 3
|Department||Humanities, Social and Political Sciences|
|851-0252-04L||Behavioral Studies Colloquium||0 credits||2K||C. Stadtfeld, U. Brandes, H.‑D. Daniel, T. Elmer, C. Hölscher, M. Kapur, H. Nax, R. Schubert, E. Stern|
|Abstract||This colloquium is about recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan.|
|Objective||Participants are informed about recent and ongoing research in the field. Presenting doctoral students obtain feedback on their dissertation research plan.|
|Content||The covers the broadly understood field of behavioral science, including theoretical as well as empirical research 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.|
|Prerequisites / Notice||Doctoral students in D-GESS can obtain 2 credits for presenting their dissertation research plan.|
|851-0585-41L||Computational Social Science |
Number of participants limited to 50.
|3 credits||2S||H. Nax|
|Abstract||The 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.|
|Objective||Participants 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.