Rhodes, D.M., Holcombe, M. and Qwarnstrom, E.E. orcid.org/0000-0003-4417-8663 (2016) Reducing complexity in an agent based reaction model-Benefits and limitations of simplifications in relation to run time and system level output. Biosystems, 147. pp. 21-27. ISSN 0303-2647
Abstract
Agent based modelling is a methodology for simulating a variety of systems across a broad spectrum of fields. However, due to the complexity of the systems it is often impossible or impractical to model them at a one to one scale. In this paper we use a simple reaction rate model implemented using the FLAME framework to test the impact of common methods for reducing model complexity such as reducing scale, increasing iteration duration and reducing message overheads. We demonstrate that such approaches can have significant impact on simulation runtime albeit with increasing risk of aberrant system behaviour and errors, as the complexity of the model is reduced.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Authors. Published by Elsevier Ireland Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Agent-based computational model; Complexity; Iterations; Limitations; Model reduction; Runtime; Scale |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Infection, Immunity and Cardiovascular Disease |
Funding Information: | Funder Grant number BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL (BBSRC) BB/J009687/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Jul 2016 09:19 |
Last Modified: | 24 Jul 2018 12:44 |
Published Version: | http://dx.doi.org/10.1016/j.biosystems.2016.06.002 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.biosystems.2016.06.002 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101796 |