Systems dynamics or agent-based modelling for immune simulation?
In immune system simulation there are two competing simulation approaches: System Dynamics Simulation (SDS) and Agent-Based Simulation (ABS). In the literature there is little guidance on how to choose the best approach for a specific immune problem. Our overall research aim is to develop a framewor...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Section |
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Springer
2011
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| Online Access: | https://eprints.nottingham.ac.uk/2030/ |
| _version_ | 1848790708577632256 |
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| author | Figueredo, Grazziela P. Aickelin, Uwe Siebers, Peer-Olaf |
| author2 | Liò, Pietro |
| author_facet | Liò, Pietro Figueredo, Grazziela P. Aickelin, Uwe Siebers, Peer-Olaf |
| author_sort | Figueredo, Grazziela P. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In immune system simulation there are two competing simulation approaches: System Dynamics Simulation (SDS) and Agent-Based Simulation (ABS). In the literature there is little guidance on how to choose the best approach for a specific immune problem. Our overall research aim is to develop a framework that helps researchers with this choice.
In this paper we investigate if it is possible to easily convert simulationmodels between approaches. With no explicit guidelines available fromthe literature we develop and test our own set of guidelines for convertingSDS models into ABS models in a non-spacial scenario. We also define
guidelines to convert ABS into SDS considering a non-spatial and a spatial scenario. After running some experiments with the developed models we found that in all cases there are significant differences between the
results produced by the different simulation methods. |
| first_indexed | 2025-11-14T18:16:55Z |
| format | Book Section |
| id | nottingham-2030 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:16:55Z |
| publishDate | 2011 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-20302024-11-08T14:54:19Z https://eprints.nottingham.ac.uk/2030/ Systems dynamics or agent-based modelling for immune simulation? Figueredo, Grazziela P. Aickelin, Uwe Siebers, Peer-Olaf In immune system simulation there are two competing simulation approaches: System Dynamics Simulation (SDS) and Agent-Based Simulation (ABS). In the literature there is little guidance on how to choose the best approach for a specific immune problem. Our overall research aim is to develop a framework that helps researchers with this choice. In this paper we investigate if it is possible to easily convert simulationmodels between approaches. With no explicit guidelines available fromthe literature we develop and test our own set of guidelines for convertingSDS models into ABS models in a non-spacial scenario. We also define guidelines to convert ABS into SDS considering a non-spatial and a spatial scenario. After running some experiments with the developed models we found that in all cases there are significant differences between the results produced by the different simulation methods. Springer Liò, Pietro Nicosia, Giuseppe Stibor, Thomas 2011 Book Section PeerReviewed Figueredo, Grazziela P., Aickelin, Uwe and Siebers, Peer-Olaf (2011) Systems dynamics or agent-based modelling for immune simulation? In: Artificial immune systems: 10th international conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011: proceedings. Lecture notes in computer science (6825). Springer, Heidelberg, pp. 81-94. ISBN 9783642223716 http://link.springer.com/chapter/10.1007/978-3-642-22371-6_10 https://doi.org/10.1007/978-3-642-22371-6_10 https://doi.org/10.1007/978-3-642-22371-6_10 |
| spellingShingle | Figueredo, Grazziela P. Aickelin, Uwe Siebers, Peer-Olaf Systems dynamics or agent-based modelling for immune simulation? |
| title | Systems dynamics or agent-based modelling for immune simulation? |
| title_full | Systems dynamics or agent-based modelling for immune simulation? |
| title_fullStr | Systems dynamics or agent-based modelling for immune simulation? |
| title_full_unstemmed | Systems dynamics or agent-based modelling for immune simulation? |
| title_short | Systems dynamics or agent-based modelling for immune simulation? |
| title_sort | systems dynamics or agent-based modelling for immune simulation? |
| url | https://eprints.nottingham.ac.uk/2030/ https://eprints.nottingham.ac.uk/2030/ https://eprints.nottingham.ac.uk/2030/ |