Feeding the beast: Can computational demographic models free us from the tyranny of data?
Silverman, Eric, Bijak, Jakub and Noble, Jason (2011) Feeding the beast: Can computational demographic models free us from the tyranny of data? In, Lenaerts, Tom, Giacobini, Mario, Bersini, Hugues, Bourgine, Paul, Dorigo, Marco and Doursat, René (eds.) Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems. , MIT Press, 747-754.
Since its inception, ALife has moved from producing large numbers of highly-idealised, theoretical models towards greater integration with empirically collected data. In contrast, demography — the interdisciplinary study of human populations — has been largely following the principles of logical empiricism, with models driven mainly by data, and insufficient attention being paid to theoretical investigation. Such an approach reduces the ability to produce micro-level explanations of population processes, which would be coherent with the phenomena observed at the macro level, without having to rely on ever-increasing data demands of complex demographic models. In this paper we argue that by bringing ALife-inspired, agent-based methods into demographic research, we can both develop a greater understanding of the processes underlying demographic change, and avoid a limiting over-dependence on potentially immense sets of data.
|Item Type:||Book Section|
|Divisions :||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
|Accepted Date and Publication Date:||
|Date Deposited:||25 Sep 2011 15:09|
|Last Modified:||31 Mar 2016 14:22|
Centre for Population Change: Understanding Population Change in the 21st Century
Funded by: ESRC National Centre for Research Methods (RES-625-28-0001)
Led by: Jane Cecelia Falkingham
1 January 2009 to 31 December 2013
|Further Information:||Google Scholar|
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