Using machine learning as a surrogate model for agent-based simulations

Claudio Angione; Eric Silverman; Elisabeth Yaneske

doi:10.1371/journal.pone.0263150

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Peer-reviewed

Research Article

Using machine learning as a surrogate model for agent-based simulations

Claudio Angione ,

Contributed equally to this work with: Claudio Angione, Eric Silverman, Elisabeth Yaneske

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: c.angione@tees.ac.uk

Affiliations School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, United Kingdom, Healthcare Innovation Centre, Teesside University, Middlesbrough, United Kingdom, National Horizons Centre, Teesside University, Darlington, United Kingdom, Centre for Digital Innovation, Teesside University, Middlesbrough, United Kingdom

https://orcid.org/0000-0002-3140-7909

⨯
Eric Silverman ,

Contributed equally to this work with: Claudio Angione, Eric Silverman, Elisabeth Yaneske

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Institute for Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom

https://orcid.org/0000-0003-0147-6118

⨯
Elisabeth Yaneske

Contributed equally to this work with: Claudio Angione, Eric Silverman, Elisabeth Yaneske

Roles Data curation, Investigation, Software, Visualization, Writing – original draft, Writing – review & editing

Affiliation School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, United Kingdom
⨯

Using machine learning as a surrogate model for agent-based simulations

Claudio Angione,
Eric Silverman,
Elisabeth Yaneske

Published: February 10, 2022
https://doi.org/10.1371/journal.pone.0263150

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