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

Dilaver, Ozge and Gilbert, Nigel (2023) Unpacking a Black Box: A Conceptual Anatomy Framework for Agent-Based Social Simulation Models. Journal of Artificial Societies and Social Simulation, 26 (1). ISSN 1460-7425

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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.

Item Type: Article
Subjects: Impact Archive > Computer Science
Depositing User: Managing Editor
Date Deposited: 16 Oct 2023 03:37
Last Modified: 16 Oct 2023 03:37
URI: http://research.sdpublishers.net/id/eprint/2686

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