<div class="csl-bib-body">
<div class="csl-entry">Bicher, M., Viehauser, M., Giannandrea, D., Kastinger, H., Brunmeir, D., & Popper, N. (2025). <i>Novel Concepts for Agent-Based Population Modelling and Simulation: Updates from GEPOC ABM</i>. arXiv. https://doi.org/10.48550/ARXIV.2511.05637</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/230174
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dc.description.abstract
In recent years, dynamic agent-based population models, which model every inhabitant of a country as a statistically representative agent, have been gaining in popularity for decision support. This is mainly due to their high degree of flexibility with respect to their area of application. GEPOC ABM is one of these models. Developed in 2015, it is now a well-established decision support tool and has been successfully applied for a wide range of population-level research questions ranging from health-care to logistics. At least in part, this success is attributable to continuous improvement and development of new methods. While some of these are very application- or implementation-specific, others can be well transferred to other population models. The focus of the present work lies on the presentation of three selected transferable innovations. We illustrate an innovative time-update concept for the individual agents, a co-simulation-inspired simulation strategy, and a strategy for accurate model parametrisation. We describe these methods in a reproducible manner, explain their advantages and provide ideas on how they can be transferred to other population models.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.description.sponsorship
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.subject
modeling
en
dc.subject
population
en
dc.subject
demography
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dc.subject
simulation
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dc.title
Novel Concepts for Agent-Based Population Modelling and Simulation: Updates from GEPOC ABM
en
dc.type
Preprint
en
dc.type
Preprint
de
dc.identifier.arxiv
2511.05637
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dc.contributor.affiliation
dwh GmbH, Austria
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dc.relation.grantno
I 5908-G
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dc.relation.grantno
LS22-071
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dc.relation.grantno
918405
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tuw.project.title
Pro-Active Routing for Emergency Testing in Pandemics
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tuw.project.title
Being Equipped to Tackle Epidemics Right
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tuw.project.title
Agent-Based Population Simulation for Resilience against Climate Change and Related Emergencies