COMPLEX SYSTEMS AND SOCIAL SIMULATIONS
SUMMER SCHOOL 2009

Central European University, Budapest, Hungary
JULY 13 - 24, 2009

www.sun.ceu.hu/complex

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

Faculty:
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
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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.