Agent-based modelling for Urban Analytics: State of the art and challenges

Malleson, N orcid.org/0000-0002-6977-0615, Birkin, M, Birks, D et al. (5 more authors) (2022) Agent-based modelling for Urban Analytics: State of the art and challenges. AI Communications, 35 (4). pp. 393-406. ISSN 0921-7126

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Copyright, Publisher and Additional Information: © 2022 – IOS Press. This is an author produced version of a paper published in AI Communications. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Multi-Agent Systems (MAS) research, Agent-Based Modelling (ABM), Urban Analytics
Dates:
  • Accepted: 22 August 2022
  • Published: 20 September 2022
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)
Funding Information:
FunderGrant number
EU - European Union757455
Depositing User: Symplectic Publications
Date Deposited: 24 Oct 2022 10:33
Last Modified: 26 Oct 2022 11:50
Status: Published
Publisher: IOS Press
Identification Number: https://doi.org/10.3233/aic-220114
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