The University of Surrey (www.surrey.ac.uk) is a research-focused University founded in 1967 with a mission that emphasizes professional and applied research. It has strong research groups in environmental science (especially life cycle analysis), the social sciences and engineering (especially space science and communications). In proportion to its size, it has the third greatest proportion of its income from research grants and contracts of all the British Universities.
The Centre for Research in Social Simulation (CRESS) (http://cress.soc.surrey.ac.uk), based in the Department of Sociology in the Faculty of Arts and Human Sciences at the University of Surrey, is a multidisciplinary centre bringing together the social sciences, software engineering and agent-based computing to promote and support the use of social simulation in research in the human sciences. CRESS is involved in a number of research projects applying simulation to policy in areas such as understanding value chains, environmental management, governance of science, web-based social networks, and basic research on modelling the evolution of social structure. It has a strong reputation in the methodology of and application of agent-based modelling. Its work has been supported by the European Commission through a number of project grants over the past 14 years and also by grants from the UK Research Councils. CRESS has extensive knowledge of computer models and modeling methods relevant to social and coupled socio-ecological-economic systems. This includes participatory modeling processes, which it has applied in a multitude of different domains and sectors.
Additionally, in the context of the ERIE project in which CRESS is currently heavily involved, it has established a network of key contacts and collected extensive knowledge on the metabolic and social networks of the Humber Region's bio-economy as well as the key causal processes driving the development of that economy. The ERIE project has also generated novel tools to enhance participatory modelling processes by improving the identification and evaluation of key “leverage points” in the system under study.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 691752.