Cross-Disciplinary Views on Modelling Complex Systems
This paper summarises work within an interdisciplinary collaboration which has explored different approaches to modelling complex systems in order to identify and develop common tools and techniques. We present an overview of the models that have been explored and the techniques that have been used by two of the partners within the project. On the one hand, there is a partner with a background in agent-based social simulation, and on the other, one with a background in equation-based modelling in theoretical physics. Together we have examined a number of problems involving complexity, modelling them using different approaches and gaining an understanding of how these alternative approaches may guide our own work. Our main finding has been that the two approaches are complimentary, and are suitable for exploring different aspects of the same problems.
KeywordsSystem Dynamic Model Social Simulation Exceptional State Modelling Complex System Rock Lake
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- 1.Holland, J.: The effect of labels (tags) on social interactions. Technical Report 93-10-064, Santa Fe Institute (1993)Google Scholar
- 2.Edmonds, B.: The emergence of symbiotic groups resulting from skill-differentiation and tags. Journal of Artificial Societies and Social Simulation 9(1), 10 (2006)Google Scholar
- 3.Hales, D.: Choose your tribe! – evolution at the next level in a peer-to-peer network. Technical Report UBLCS-2005-13, University of Bologna, Dept. of Computer Science (2005)Google Scholar
- 4.Hales, D., Arteconi, S., Babaoğlu, Ö.: Slacer: randomness to cooperation in peer-to-peer networks. In: Proceedings of the Workshop on Stochasticity in Distributed Systems (STODIS 2005) including in the Proceedings of IEEE CollaborateCom Conference, San Jose, CA (2005)Google Scholar
- 5.Norling, E., Edmonds, B.: Why it is better to be SLAC than smart. In: Proceedings of the World Congress on Social Simulation, Kyoto, Japan (2006)Google Scholar
- 8.Dunne, J.A.: The network structure of food webs. In: Pascual, M., Dunne, J.A. (eds.) Ecological Networks: Linking Structure to Dynamics in Food Webs, pp. 27–86. Oxford University Press, Oxford (2005)Google Scholar
- 14.Baxter, G., Blythe, R., Croft, W., McKane, A.: Modeling language change: An evaluation of trudgill’s theory of the emergence of new zealand english (in submission) (2008), http://www.ph.ed.ac.uk/~rblythe2/Preprints/BBCM08.pdf
- 15.Baxter, G.J., Blythe, R.A., Croft, W., McKane, A.J.: Utterance selection model of language change. Physical Review E 73 (2006)Google Scholar
- 16.Edmonds, B.: Achieving consensus among agents - an opinion-dynamics model. Technical Report CPM-08-185, Centre for Policy Modelling (2008)Google Scholar
- 19.Powell, C.R., McKane, A.J.: Effects of food web construction by evolution or immigration. Submitted to Oikos (2008)Google Scholar
- 20.Baxter, G.J., Blythe, R.A., McKane, A.J.: Fixation and consensus times on a network: a unified approach (in submission) (preprint) (2008), http://arxiv.org/abs/0801.3083
- 21.M2M 2007: Third international model-to-model workshop (2007), http://m2m2007.macaulay.ac.uk/