Dynamic calibration of agent-based models using data assimilation

A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. Fi...

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Main Authors: Jonathan A. Ward, Andrew J. Evans, Nicolas S. Malleson
Format: Article
Language:English
Published: The Royal Society 2016-01-01
Series:Royal Society Open Science
Subjects:
Online Access:https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150703
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author Jonathan A. Ward
Andrew J. Evans
Nicolas S. Malleson
author_facet Jonathan A. Ward
Andrew J. Evans
Nicolas S. Malleson
author_sort Jonathan A. Ward
collection DOAJ
description A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.
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spelling doaj.art-61fb6b06b224457a855ab519a86e97b32022-12-21T23:39:22ZengThe Royal SocietyRoyal Society Open Science2054-57032016-01-013410.1098/rsos.150703150703Dynamic calibration of agent-based models using data assimilationJonathan A. WardAndrew J. EvansNicolas S. MallesonA widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150703agent-based modelsdata assimilationcomplex systems
spellingShingle Jonathan A. Ward
Andrew J. Evans
Nicolas S. Malleson
Dynamic calibration of agent-based models using data assimilation
Royal Society Open Science
agent-based models
data assimilation
complex systems
title Dynamic calibration of agent-based models using data assimilation
title_full Dynamic calibration of agent-based models using data assimilation
title_fullStr Dynamic calibration of agent-based models using data assimilation
title_full_unstemmed Dynamic calibration of agent-based models using data assimilation
title_short Dynamic calibration of agent-based models using data assimilation
title_sort dynamic calibration of agent based models using data assimilation
topic agent-based models
data assimilation
complex systems
url https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150703
work_keys_str_mv AT jonathanaward dynamiccalibrationofagentbasedmodelsusingdataassimilation
AT andrewjevans dynamiccalibrationofagentbasedmodelsusingdataassimilation
AT nicolassmalleson dynamiccalibrationofagentbasedmodelsusingdataassimilation