Information détaillée concernant le cours
Agent-based Modelling for the Social Scientist
24-26 May 2023
|Lang||Workshop language is English|
Dr. Elisa Volpi, coordinatrice CUSO
Jennifer Badham (Durham University) and Corinna Elsenbroich (University of Glasgow)
The course has three ingredients:
All of the sessions are carefully integrated into each other to allow for a rounded learning experience. The tutorial is the heart of the course. Note that it is built in a linear way, meaning that it is important to attend every session. It is also built in such a way that it revisits relevant aspects of programming recursively – and it is important that no student works ahead by themselves as it will lead to confusion for the student and most likely hold up the whole class.
Modelling for Complex Systems
Introductory session covering general aspects of seeing society as a complex system, ways of modelling society and some classic agent-based models.
Using NetLogo and Simple Coding
First session where you get your hands dirty. The session covers what NetLogo is, how it works and how you can work with it. It also introduces you to the first steps of programming in NetLogo using a simple model.
Models, Simulation and the Modelling Process
This session provides a conceptual background to modelling. It covers conceptualisations of models and simulations as well as the process of model construction.
Why model? This session will cover different purposes for modelling and go through different specifications of models. It will in particular focus on the kinds of research questions that can (and can't) be answered with an agent-based model.
Verification, Validation, Data, Calibration
How do you know you have got a good model? This session will go through ways of assessing the quality of your model discussing internal consistency, its relationship to reality and ways to find out how good your model is.
This session will go through what needs to be done once the model has been built and checked. Models are not ends in themselves but means to answer research questions. Experiments are done to generate data to answer these questions.
The workshop will take place on three days (May 24 to May 26) from 9:00 to 16:30. For the exact schedule, please contact Elisa Volpi ([email protected]).
Genève (Graduate Institute)
Gilbert, G. N. (2007) Agent-based models. London: SAGE. Available at: eu.alma.exlibrisgroup.com/view/action/uresolver.do age_service_id=3714069910002346&institutionId=2346&customerId=2345.This is a really good, comprehensive and short introduction to agent-based modelling. Highly recommended.
Railsback, S. F. and Grimm, V. (2012) Agent-based and individual-based modeling: a practical introduction. Princeton: Princeton University Press.
Squazzoni, F., Jager, W. and Edmonds, B. (2014) 'Social Simulation in the Social Sciences', Social Science Computer Review, 32(3), pp. 279–294. doi: 10.1177/0894439313512975. A good overview of the field.
Chattoe-Brown, E. (2013) 'Why Sociology Should Use Agent Based Modelling', Sociological Research Online, 18(3), pp. 1–11. doi: 10.5153/sro.3055.
Agent-based models: understanding the economy from the bottom up | Bank of England (no date). Available at: www.bankofengland.co.uk/quarterly-bulletin/2016/q4/agent- based-models-understanding-the-economy-from-the-bottom-up.
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Elsenbroich, C. and Badham, Jennifer (2016) 'The Extortion Relationship: A Computational Analysis', Journal of Artificial Societies and Social Simulation, 19(4). Available at: jasss.soc.surrey.ac.uk/19/4/8.html.
Elsenbroich, C., & Badham, J. (2022). Negotiating a Future that is not like the Past. International Journal of Social Research Methodology
Gilbert, G. N. and Troitzsch, K. G. (2005) Simulation for the social scientist. 2nd ed. Maidenhead: Open University Press. Available at: ebookcentral.proquest.com/lib/surrey/detail.action.
Natarajan, S., Padget, J. and Elliott, L. (2011) 'Modelling UK domestic energy and carbon emissions: an agent-based approach', Energy and Buildings, 43(10), pp. 2602–2612. doi: 10.1016/j.enbuild.2011.05.013.
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Axelrod, Robert (1986), An Evolutionary Approach to Norms, American Political Science Review, Vol. 80, pp. 1095-1111
Gilbert, N., Hawksworth, J. C. and Swinney, P. A. (2008) An agent-based model of the UK housing market. Technical report, CRESS University of Surrey.
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Squazzoni, F. (2010) The impact of agent-based models in the social sciences after 15 years of incursions. History of Economic Ideas, XVIII(2).
Jager, W. (2017) 'Enhancing the Realism of Simulation (EROS): On Implementing and Developing Psychological Theory in Social Simulation', Journal of Artificial Societies and Social Simulation, 20(3). Available at: jasss.soc.surrey.ac.uk/20/3/14.html.
Macy, M. W. and Willer, R. (2002) 'From Factors to Factors: Computational Sociology and Agent-Based Modeling', Annual Review of Sociology, 28(1), pp. 143–166. doi: 10.1146/annurev.soc.28.110601.141117.
Squazzoni, F.(2010) 'THE IMPACT OF AGENT-BASED MODELS IN THE SOCIAL SCIENCES AFTER 15 YEARS OF INCURSIONS', History of Economic Ideas. Accademia Editoriale, 18(2), pp. 197– 233. Available at: www.jstor.org/stable/23723517.
Wilensky, U. and Rand, W. (2015) An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with NetLogo. Cambridge, Massachusetts: MIT Press. Available at: ebookcentral.proquest.com/lib/surrey/detail.action