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Future developments in geographical agent‐based models: challenges and opportunities

Heppenstall, A. , Crooks, A., Malleson, N., Manley, E., Ge, J. and Batty, M. (2021) Future developments in geographical agent‐based models: challenges and opportunities. Geographical Analysis, 53(1), pp. 76-91. (doi: 10.1111/gean.12267) (PMID:33678813) (PMCID:PMC7898830)

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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.

Item Type:Articles
Additional Information:50th Anniversary Special Issue.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Heppenstall, Professor Alison
Authors: Heppenstall, A., Crooks, A., Malleson, N., Manley, E., Ge, J., and Batty, M.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Geographical Analysis
Publisher:Wiley on behalf of The Ohio State University
ISSN:0016-7363
ISSN (Online):1538-4632
Published Online:04 December 2020
Copyright Holders:Copyright © 2020 The Author(s)
First Published:First published in Geographical Analysis 53(1):76-91
Publisher Policy:Reproduced under a creative commons licence

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