Streamlining simulation experiments with agent-based models in demography
Streamlining simulation experiments with agent-based models in demography
In the last decade, the uptake of agent-based modeling in demography and other population sciences has been slowly increasing. Still, in such areas, where traditional data-driven, statistical approaches prevail, the hypothesis-driven design of agent-based models leads to questioning the validity of these models. Consequently, suitable means to increase the confidence into models and simulation results are required. To that end, explicit, replicable simulation experiments play a central role in model design and validation. However, the analysis of more complex models implies executing various experiments, each of which combines various methods. To streamline these experimentation processes a flexible computational simulation environment is necessary. With a new binding between SESSL – an internal domain-specific language for simulation experiments – and ML3 – a simulator for linked lives designed specifically for agent-based demographic models – we cater for these objectives and provide a powerful simulation tool. The proposed approach can serve as a foundation for current efforts of employing advanced and statistical model analysis of agent-based demographic models, as part of a wider process of iterative model building. We demonstrate its potential in specifying and executing different experiments with a simple model of return migration and a more complex model of social care.
Agent-based modeling, Demography, Meta-modeling, Simulation experimentation
Reinhardt, Oliver
8137d512-1d8e-45ef-9346-8a117ebdfd4b
Hilton, Jason D.
da31e515-1e34-4e9f-846d-633176bb3931
Warnke, Tom
de53eb21-3a88-4593-98ca-8c547ac7bd77
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Uhrmacher, Adelinde M.
4fa04994-ea2b-4a1a-bf1e-5e7897359d28
30 June 2018
Reinhardt, Oliver
8137d512-1d8e-45ef-9346-8a117ebdfd4b
Hilton, Jason D.
da31e515-1e34-4e9f-846d-633176bb3931
Warnke, Tom
de53eb21-3a88-4593-98ca-8c547ac7bd77
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Uhrmacher, Adelinde M.
4fa04994-ea2b-4a1a-bf1e-5e7897359d28
Reinhardt, Oliver, Hilton, Jason D., Warnke, Tom, Bijak, Jakub and Uhrmacher, Adelinde M.
(2018)
Streamlining simulation experiments with agent-based models in demography.
JASSS, 21 (3), [9].
(doi:10.18564/jasss.3784).
Abstract
In the last decade, the uptake of agent-based modeling in demography and other population sciences has been slowly increasing. Still, in such areas, where traditional data-driven, statistical approaches prevail, the hypothesis-driven design of agent-based models leads to questioning the validity of these models. Consequently, suitable means to increase the confidence into models and simulation results are required. To that end, explicit, replicable simulation experiments play a central role in model design and validation. However, the analysis of more complex models implies executing various experiments, each of which combines various methods. To streamline these experimentation processes a flexible computational simulation environment is necessary. With a new binding between SESSL – an internal domain-specific language for simulation experiments – and ML3 – a simulator for linked lives designed specifically for agent-based demographic models – we cater for these objectives and provide a powerful simulation tool. The proposed approach can serve as a foundation for current efforts of employing advanced and statistical model analysis of agent-based demographic models, as part of a wider process of iterative model building. We demonstrate its potential in specifying and executing different experiments with a simple model of return migration and a more complex model of social care.
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More information
Accepted/In Press date: 8 June 2018
e-pub ahead of print date: 30 June 2018
Published date: 30 June 2018
Keywords:
Agent-based modeling, Demography, Meta-modeling, Simulation experimentation
Identifiers
Local EPrints ID: 423064
URI: http://eprints.soton.ac.uk/id/eprint/423064
ISSN: 1460-7425
PURE UUID: 5913e09e-7dc8-492a-91ba-3a4dbfd62491
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Date deposited: 13 Aug 2018 16:30
Last modified: 06 Jun 2024 01:49
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Contributors
Author:
Oliver Reinhardt
Author:
Tom Warnke
Author:
Adelinde M. Uhrmacher
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