Complex systems, Computer science, Economics, Political science, Sociology

This course is sponsored by:



Course date

7 July - 18 July, 2008
Application deadline
15 February, 2008
Course Director(s): 

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
Course Faculty: 

Iqbal Adjali

Unilever Corporate Research, Colworth, UK

Petra Ahrweiler

Innovation Research Unit, CASL, University College Dublin (UCD), Ireland

Stefano Battiston

Swiss Federal Institute of Technology, System Design, Zurich, Switzerland

Lars Eric Cederman

Institute for International Conflict Research, Swiss Federal Institute of Technology, Zurich, Switzerland

Krzysztof Kurowski

Institute of Bioorganic Chemistry, PAS, Supercomputing and Networking Center, Poznan, Poland

Flaminio Squazzoni

University of Brescia, Social Sciences, Italy

Klaus G. Troitzsch

University of Koblenz-Landau, Institute for IS Research, Germany

Balazs Vedres

Central European University, Sociology and Social Anthropology, Budapest, Hungary

The summer course 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.