Streamlining Simulation Experiments with Agent-Based Models in Demography

Oliver Reinhardt (), Jason Hilton (), Tom Warnke (), Jakub Bijak () and Adelinde M. Uhrmacher ()
Additional contact information
Oliver Reinhardt: https://mosi.informatik.uni-rostock.de/en/group/staff/reinhardt/
Jason Hilton: https://www.southampton.ac.uk/socsci/about/staff/jdh1d15.page
Tom Warnke: https://mosi.informatik.uni-rostock.de/en/group/staff/warnke/
Jakub Bijak: https://www.southampton.ac.uk/socsci/about/staff/jb1d08.page
Adelinde M. Uhrmacher: https://mosi.informatik.uni-rostock.de/en/group/staff/uhrmacher/

Journal of Artificial Societies and Social Simulation, 2018, vol. 21, issue 3, 9

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.

Keywords: Agent-Based Modeling; Demography; Simulation Experimentation; Meta-Modeling (search for similar items in EconPapers)
Date: 2018-06-30
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Citations: View citations in EconPapers (2)

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