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How to Relate Models to Reality? An Epistemological Framework for the Validation and Verification of Computational Models

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Abstract

Agent-based simulations have become increasingly prominent in various disciplines. This trend is positive, but it comes with challenges: while there are more and more standards for design, verification, validation, and presentation of the models, the various meta-theoretical strategies of how the models should be related to reality often remain implicit. Differences in the epistemological foundations of models make it however, difficult to relate distinct models to each other and to ensure a cumulative expansion of knowledge. Concepts and the analytic language developed by philosophers of science can help to overcome these obstacles. This paper introduces some of these concepts to the modelling community. It also presents an epistemological framework that helps to clarify how one wishes to generate knowledge about reality by the means of one's model and that helps to relate models to each other. Since the interpretation of a model is strongly connected to the activities of model verification and validation, these two activities will be embedded into the framework and their respective epistemological roles will be clarified. The resulting meta-theoretical framework aligns well with recently proposed frameworks for model presentation and evaluation.

Suggested Citation

  • Claudius Graebner, 2018. "How to Relate Models to Reality? An Epistemological Framework for the Validation and Verification of Computational Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(3), pages 1-8.
  • Handle: RePEc:jas:jasssj:2017-113-3
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    Cited by:

    1. Kristoffer Wikstrom & Hal T. Nelson, 2022. "Spatial Validation of Agent-Based Models," Sustainability, MDPI, vol. 14(24), pages 1-13, December.
    2. Claudius Gräbner & Wolfram Elsner & Alex Lascaux, 2021. "Trust and Social Control: Sources of Cooperation, Performance, and Stability in Informal Value Transfer Systems," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1077-1102, December.
    3. Claudius Gräbner & Birte Strunk, 2020. "Pluralism in economics: its critiques and their lessons," Journal of Economic Methodology, Taylor & Francis Journals, vol. 27(4), pages 311-329, October.
    4. Miguel Riviere & Sylvain Caurla, 2020. "Representations of the Forest Sector in Economic Models [Les représentations du secteur forestier dans les modèles économiques]," Post-Print hal-03088084, HAL.
    5. Patrick Mellacher, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," Papers 2011.06289, arXiv.org.
    6. Felder, F.A. & Kumar, P., 2021. "A review of existing deep decarbonization models and their potential in policymaking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    7. Claudius Graebner & Amineh Ghorbani, 2019. "Defining institutions - A review and a synthesis," ICAE Working Papers 89, Johannes Kepler University, Institute for Comprehensive Analysis of the Economy.

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