Heppenstall, A orcid.org/0000-0002-0663-3437, Crooks, A, Malleson, N orcid.org/0000-0002-6977-0615 et al. (3 more authors) (2021) Future Developments in Geographical Agent‐Based Models: Challenges and Opportunities. Geographical Analysis, 53 (1). pp. 76-91. ISSN 0016-7363
Abstract
Despite reaching a point of acceptance as a research tool across the geographical and social sciences, there remain significant methodological challenges for agent‐based models. These include recognizing and simulating emergent phenomena, agent representation, construction of behavioral rules, and calibration and validation. While advances in individual‐level data and computing power have opened up new research avenues, they have also brought with them a new set of challenges. This article reviews some of the challenges that the field has faced, the opportunities available to advance the state‐of‐the‐art, and the outlook for the field over the next decade. We argue that although agent‐based models continue to have enormous promise as a means of developing dynamic spatial simulations, the field needs to fully embrace the potential offered by approaches from machine learning to allow us to fully broaden and deepen our understanding of geographical systems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Geographical Analysis published by Wiley Periodicals LLC on behalf of The Ohio State University. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Nov 2020 12:50 |
Last Modified: | 17 Jul 2021 22:32 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/gean.12267 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168143 |
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