Complex systems and social simulations summer school 2009
Central European University, Budapest, Hungary, JULY 13 – 24, 2009.
Application deadline: 5 March, 2009
Course Directors:
Laszlo Gulyas, Collegium Budapest / ELTE, Department of History and Philosophy of Science, Hungary
Gyorgy Kampis, Collegium Budapest, Focus Group on the Philosophy of Complexity / ELTE, Department of History and Philosophy of Science, Hungary
Petra Arhweiler, University of Hamburg / University of Bielefeld, Faculty of Sociology, Germany
Albert-Laszlo Barabasi, Northeastern University, Department of Physics / Center for Cancer Systems Biology, Dana Farber Cancer Institute, Harvard University, US
Flaminio Squazzoni, (to be confirmed)
Ferenc Jordan, Animal Ecology Research Group of the Hungarian Academy of Sciences (HAS), Budapest, Hungary
Imre Kondor, Collegium Budapest, Hungary
Scott Page, University of Michigan, Ann Arbor, USA
Klaus G. Troitzsch, University of Koblenz-Landau, Germany
Balazs Vedres, CEU, Center for Network Science, Budapest, Hungary
The summer school is aimed at providing a state-of-the-art cutting-edge scientific and research-oriented training for junior faculty, young researchers, postdoctoral fellows, MA and Ph.D. students, and professionals from European and overseas universities and research institutes on complex systems and social simulations.
The term Complex Systems (CSS) denotes an interdisciplinary research methodology currently successful in the social sciences and elsewhere. CS research originated from physics and nonlinear systems some decades ago but its models have soon permeated such distant fields as economy, political science or more recently sociology. As implied by the name, a CS is essentially a system of many complicated interactions. Complex Systems methodology has developed sophisticated yet well understood tools to cope with this challenge. In social systems the essence of CS is the characterization of the distributed dynamics of how the interaction of many actors and variables leads to predictable phenomena, which often involve hierarchy, emergence, dynamic structures and large scale transitions.
Each day in the course focuses on one tool of this encompassing methodology. CS methods include various mathematical models (nonlinear systems, networks, statistical approaches), computer simulations (e.g. systems dynamics, agent-based modeling). CS simulations are highly computation intensive and pose problems of supercomputing and parallelization.
The CSSS course offers lectures, tutorials and discussions on the whole spectrum of the above. Lectures are from leading experts, specifically focusing on CS concepts, modeling and (social) simulation, followed by discussion.

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