Feeding the beast: can computational demographic models free us from the tyranny of data?
Feeding the beast: can computational demographic models free us from the tyranny of data?
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
0-262-29714-0
747-754
Silverman, Eric
641120a2-6584-46a6-a33b-4ea9133463af
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Noble, Jason
440f07ba-dbb8-4d66-b969-36cde4e3b764
8 August 2011
Silverman, Eric
641120a2-6584-46a6-a33b-4ea9133463af
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Noble, Jason
440f07ba-dbb8-4d66-b969-36cde4e3b764
Silverman, Eric, Bijak, Jakub and Noble, Jason
(2011)
Feeding the beast: can computational demographic models free us from the tyranny of data?
Lenaerts, Tom, Giacobini, Mario, Bersini, Hugues, Bourgine, Paul, Dorigo, Marco and Doursat, Rene
(eds.)
In Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems.
MIT Press.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
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
Text
feedingTheBeast.pdf
- Accepted Manuscript
Restricted to Repository staff only
Request a copy
Text
feedingTheBeast.pdf
- Other
Restricted to Repository staff only
Request a copy
More information
Published date: 8 August 2011
Venue - Dates:
conference; fr; 2011-08-08; 2011-08-12, Paris, France, 2011-08-08 - 2011-08-12
Organisations:
Social Statistics & Demography, Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 208395
URI: http://eprints.soton.ac.uk/id/eprint/208395
ISBN: 0-262-29714-0
PURE UUID: 720b04a0-22dd-4073-b002-c1f6a390ac98
Catalogue record
Date deposited: 20 Jan 2012 14:41
Last modified: 15 Mar 2024 03:34
Export record
Contributors
Author:
Eric Silverman
Author:
Jason Noble
Editor:
Tom Lenaerts
Editor:
Mario Giacobini
Editor:
Hugues Bersini
Editor:
Paul Bourgine
Editor:
Marco Dorigo
Editor:
Rene Doursat
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
