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, Rene (eds.) Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems. Cambridge, US, MIT Press, 747-754.
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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|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science
H Social Sciences > HA Statistics
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
Faculty of Social and Human Sciences > Social Sciences > Social Statistics & Demography
|Date Deposited:||20 Jan 2012 14:41|
|Last Modified:||02 Mar 2012 13:18|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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