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Negotiating a Future that is not like the Past

Elsenbroich, Corinna and Badham, Jennifer (2022) 'Negotiating a Future that is not like the Past.', International Journal of Social Research Methodology .

Abstract

Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important in modelling dynamic complex systems, where the past is not a reliable blueprint for the future. By balancing theory and data, agent-based modelling is a tool to describe plausible futures, that we call “justified stories”. We conclude that this balance must be maintained if agent-based models are to serve a useful decision support role for policy makers.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial 4.0.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1080/13645579.2022.2137935
Publisher statement:© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date accepted:01 September 2022
Date deposited:14 October 2022
Date of first online publication:04 November 2022
Date first made open access:06 January 2023

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