Abstract
The problem of social simulation is analysed, identifying what I call ‘syntactic’ and ‘semantic’ complexity. These mean that social simulation has particular needs in terms of computational tools. I suggest an approach where one identifies, documents and checks constraints from a variety of sources. Eight criteria for a computational tool to support social simulation are proposed and illustrated using the language SDML. I speculate that a general tool for developing, running and comparing sets of models and results could greatly aid social simulation. This would help manage the clusters of closely related models that social systems seem to necessitate.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Axelrod, R., Epstein, J. M. and Cohen, M. D. (1996) Aligning Simulation Models: A Case Study and Results. Computational and Mathematical Organization Theory, 1.
Axtell, R. L. and J. M. Epstein (1994). Agent-based Modelling: Understanding our Creations. The Bulletin of the Santa Fe Institute 9: 28–32.
Brazier, F. M. T., Dunin-Keplicz, B. M., Jennings, N. R. and Treur, J. (1997), DESIRE: Modelling Multi-Agent Systems in a Compositional Formal Framework, International Journal of Cooperative Information Systems, 6:67–94.
Cartwright, N. (1983). How the Laws of Physics Lie. Oxford, Clarendon Press.
Conte, R., Hegselman, R. and Terna, P. (1997) Simulating Social Phenomena, Springer: Lecture Notes in Economics and Mathematical Systems, 456.
Cooper, R., J. Fox, et al. (1997). A Systematic Methodology for Cognitive Modelling. Artificial Intelligence 85: 3–44.
Edmonds, B. (1999). Pragmatic Holism. Foundations of Science 4:57–82.
Edmonds, B. (1999). Syntactic Measures of Complexity. Doctoral Thesis, University of Manchester, Manchester, UK.
Edmonds, B. (2000). The Use of Models-making MABS actually work. In S. Moss and P. Davidsson (eds.) Multi Agent Based Simulation. Berlin: Springer-Verlag. Lecture Notes in Artificial Intelligence, 1979:15–3.
Giere Ronald, N. (1988). Explaining science: a cognitive approach. Chicago; London, University of Chicago Press.
Gilbert, N. (1995) Emergence in Social Simulation. In (Gilbert and Conte 1995), 144–156.
Gilbert, N. and Doran, J. (1994) Simulating societies: the computer simulation of social phenomena. London: UCL Press.
Gilbert, N. and Conte, R. (1995) Artificial societies: the computer simulation of social life. London: UCL Press.
Holland John, H. (1998). Emergence: from chaos to order. Oxford; New York, Oxford University Press.
Konolige, K. (1992). Autoepistemic Logic. In D. Gabbay, C. Hogger and J. Robinson. (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 3. Oxford, Clarendon. 217–295.
Lakatos, I. (1983). The methodology of scientific research programmes. Cambridge, Cambridge University Press.
Mariotto, M. B., Nuno, D., Sichman, J. S. and Coelho, H. (2002) Requirements Analysis of Agent-Based Simulation Platforms: State of the Art and New Prospects, this volume.
Moss, S., H. Gaylard, & al. (1996). SDML: A Multi-Agent Language for Organizational Modelling. Computational and Mathematical Organization Theory 4(1): 43–69.
Schelling, Thomas C. (1971). Dynamic Models of Segregation. Journal of Mathematical Sociology 1:143–186.
Simon, H.A. (1986). The failure of armchair economics [Interview]. Challenge, 29(5), 18–25.
Suppes, P. (1962). Models of Data. In Nagel, E. et al. (eds.) Logic Methodology and the Philosophy of Science: Proceedings of the 1960 International Conference. Stanford, CA: Stanford University Press, 252–261.
Terán, O., Edmonds, B. & Wallis, S. (2001) Mapping the Envelope of Social Simulation Trajectories. Multi Agent Based Simulation 2000 (MABS2000), Boston, MA, July, 2000. Lecture Notes in Artificial Intelligence, 1979:229–243.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Edmonds, B. (2003). Towards an Ideal Social Simulation Language. In: Simão Sichman, J., Bousquet, F., Davidsson, P. (eds) Multi-Agent-Based Simulation II. MABS 2002. Lecture Notes in Computer Science(), vol 2581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36483-8_8
Download citation
DOI: https://doi.org/10.1007/3-540-36483-8_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00607-7
Online ISBN: 978-3-540-36483-2
eBook Packages: Springer Book Archive