Dealing with uncertainty in agent-based models for short-term predictions

Kieu, L-M, Malleson, N and Heppenstall, A orcid.org/0000-0002-0663-3437 (2020) Dealing with uncertainty in agent-based models for short-term predictions. Royal Society Open Science, 7 (1). 191074. ISSN 2054-5703

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Keywords: agent-based modelling; data assimilation; model calibration; complex systems
Dates:
  • Accepted: 28 November 2019
  • Published (online): 15 January 2020
  • Published: 15 January 2020
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
ESRC (Economic and Social Research Council)ES/R007918/1
Alan Turing InstituteNot Known
Depositing User: Symplectic Publications
Date Deposited: 16 Dec 2019 11:35
Last Modified: 02 Mar 2020 14:47
Status: Published
Publisher: The Royal Society
Identification Number: https://doi.org/10.1098/rsos.191074
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