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dc.contributor.authorBithell, Michaelen
dc.contributor.authorEdmonds, Bruceen
dc.date.accessioned2021-10-18T23:31:02Z
dc.date.available2021-10-18T23:31:02Z
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329597
dc.description.abstractThe recent Covid crisis has led to a surge of new model development and a renewed interest in the use of models as policy tools. While this is in some senses welcome, the sudden appearance of many new models presents a problem in terms of their assessment, the appropriateness of their application and reconciling any differences in outcome. Even if they appear similar, their underlying assumptions may differ, their initial data might not be the same, policy options may be applied in different ways, stochastic effects explored to a varying extent, and model outputs presented in any number of different forms. As a result, it can be unclear what aspects of variations in output between models are results of mechanistic, parameter or data differences. Any comparison between models is made tricky by differences in experimental design and selection of output measures.
dc.rightsAll rights reserved
dc.titleTHE SYSTEMATIC COMPARISON OF AGENT-BASED POLICY MODELS– IT’S TIME WE GOT OUR ACT TOGETHER!en
dc.typeArticle
prism.publicationNameReview of Artificial Societies and Social Simulationen
dc.identifier.doi10.17863/CAM.77046
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.typeJournal Article/Reviewen
cam.issuedOnline2021-05-11en
cam.orpheus.counter11*
rioxxterms.freetoread.startdate2022-05-11


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