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Unpacking a Black Box: A Conceptual Anatomy Framework for Agent-Based Social Simulation Models

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Abstract

This paper aims to improve the transparency of agent-based social simulation (ABSS) models and make it easier for various actors engaging with these models to make sense of them. It studies what ABSS is and juxtaposes its basic conceptual elements with insights from the agency/structure debate in social theory to propose a framework that captures the ‘conceptual anatomy’ of ABSS models in a simple and intuitive way. The five elements of the framework are: agency, social structure, environment, actions and interactions, and temporality. The paper also examines what is meant by the transparency or opacity of ABSS in the rapidly growing literature on the epistemology of computer simulations. It deconstructs the methodological criticism that ABSS models are black boxes by identifying multiple categories of transparency/opacity. It argues that neither opacity nor transparency is intrinsic to ABSS. Instead, they are dependent on research habitus - practices that are developed in a research field that are shaped by structure of the field and available resources. It discusses the ways in which thinking about the conceptual anatomy of ABSS can improve its transparency.

Suggested Citation

  • Ozge Dilaver & Nigel Gilbert, 2023. "Unpacking a Black Box: A Conceptual Anatomy Framework for Agent-Based Social Simulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(1), pages 1-4.
  • Handle: RePEc:jas:jasssj:2018-42-4
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    References listed on IDEAS

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    1. Robert Axtell, 2005. "The Complexity of Exchange," Economic Journal, Royal Economic Society, vol. 115(504), pages 193-210, June.
    2. J. Gareth Polhill & Dawn C. Parker & Daniel Brown & Volker Grimm, 2008. "Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-3.
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    Cited by:

    1. Priscilla Avegliano & Jaime Simão Sichman, 2023. "Equation-Based Versus Agent-Based Models: Why Not Embrace Both for an Efficient Parameter Calibration?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(4), pages 1-3.

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