How to Describe Agent-Based Models in Population Studies?

Jürgen Groeneveld (), Anna Klabunde, Michelle L. O’Brien and André Grow
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Jürgen Groeneveld: Helmholtz Centre for Environmental Research – UFZ, Department of Ecological Modelling
Anna Klabunde: Max Planck Institute for Demographic Research
Michelle L. O’Brien: University of Washington, Department of Sociology
André Grow: University of Leuven (KU Leuven), Centre for Sociological Research

Chapter Chapter 9 in Agent-Based Modelling in Population Studies, 2017, pp 237-254 from Springer

Abstract: Abstract Agent-based models (ABMs) are increasingly used to describe, understand and predict human behaviour. The flexibility of agent-based models allows exploring mechanisms and feedback effects. However, this flexibility comes at a price, which is the problem of communicating and describing the model in a concise and transparent manner. There is no general agreement or culture yet on how agent-based models should be documented and described. Therefore, we want to contribute to the discussion on how agent-based models should be described in this position paper from a demographic perspective. Firstly we present and discuss the plethora of different ways to describe published agent-based models in population studies and demography. Subsequently, we argue that the ODD + D (Overview, Design, Details + Decisions) protocol is apt to address the specific difficulties which arise in describing demographic ABMs. We describe the main elements of the ODD + D protocol and subsequently present the results of an experiment illustrating its usefulness to describe an agent-based model of circular migration. We conclude that protocols such as the ODD + D are not only useful to compile a model description, but also serve as tool for the model developer to check if she has provided all necessary information that allows the reader to fully understand and replicate the model.

Keywords: Unify Modelling Language; Model Description; Online Appendix; Verbal Description; European Food Safety Authority (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-319-32283-4_9

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DOI: 10.1007/978-3-319-32283-4_9

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