A method for representing and developing process models
Scientists investigate the dynamics of complex systems with quantitative models, employing them to synthesize knowledge, to explain observations, and to forecast future system behavior. Complete specification of systems is impossible, so models must be simplified abstractions. Thus, the art of model...
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ftdatacite:10.48550/arxiv.q-bio/0605025 2023-05-15T18:07:33+02:00 A method for representing and developing process models Borrett, S. R. Bridewell, W. Langely, P. Arrigo, K. R. 2006 https://dx.doi.org/10.48550/arxiv.q-bio/0605025 https://arxiv.org/abs/q-bio/0605025 unknown arXiv Assumed arXiv.org perpetual, non-exclusive license to distribute this article for submissions made before January 2004 http://arxiv.org/licenses/assumed-1991-2003/ Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences Preprint Article article CreativeWork 2006 ftdatacite https://doi.org/10.48550/arxiv.q-bio/0605025 2022-04-01T17:38:35Z Scientists investigate the dynamics of complex systems with quantitative models, employing them to synthesize knowledge, to explain observations, and to forecast future system behavior. Complete specification of systems is impossible, so models must be simplified abstractions. Thus, the art of modeling involves deciding which system elements to include and determining how they should be represented. We view modeling as search through a space of candidate models that is guided by model objectives, theoretical knowledge, and empirical data. In this contribution, we introduce a method for representing process-based models that facilitates the discovery of models that explain observed behavior. This representation casts dynamic systems as interacting sets of processes that act on entities. Using this approach, a modeler first encodes relevant ecological knowledge into a library of generic entities and processes, then instantiates these theoretical components, and finally assembles candidate models from these elements. We illustrate this methodology with a model of the Ross Sea ecosystem. : submitted to Ecological Complexity 28 pages, 9 tables, 1 figure Report Ross Sea DataCite Metadata Store (German National Library of Science and Technology) Ross Sea |
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DataCite Metadata Store (German National Library of Science and Technology) |
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topic |
Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences |
spellingShingle |
Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences Borrett, S. R. Bridewell, W. Langely, P. Arrigo, K. R. A method for representing and developing process models |
topic_facet |
Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences |
description |
Scientists investigate the dynamics of complex systems with quantitative models, employing them to synthesize knowledge, to explain observations, and to forecast future system behavior. Complete specification of systems is impossible, so models must be simplified abstractions. Thus, the art of modeling involves deciding which system elements to include and determining how they should be represented. We view modeling as search through a space of candidate models that is guided by model objectives, theoretical knowledge, and empirical data. In this contribution, we introduce a method for representing process-based models that facilitates the discovery of models that explain observed behavior. This representation casts dynamic systems as interacting sets of processes that act on entities. Using this approach, a modeler first encodes relevant ecological knowledge into a library of generic entities and processes, then instantiates these theoretical components, and finally assembles candidate models from these elements. We illustrate this methodology with a model of the Ross Sea ecosystem. : submitted to Ecological Complexity 28 pages, 9 tables, 1 figure |
format |
Report |
author |
Borrett, S. R. Bridewell, W. Langely, P. Arrigo, K. R. |
author_facet |
Borrett, S. R. Bridewell, W. Langely, P. Arrigo, K. R. |
author_sort |
Borrett, S. R. |
title |
A method for representing and developing process models |
title_short |
A method for representing and developing process models |
title_full |
A method for representing and developing process models |
title_fullStr |
A method for representing and developing process models |
title_full_unstemmed |
A method for representing and developing process models |
title_sort |
method for representing and developing process models |
publisher |
arXiv |
publishDate |
2006 |
url |
https://dx.doi.org/10.48550/arxiv.q-bio/0605025 https://arxiv.org/abs/q-bio/0605025 |
geographic |
Ross Sea |
geographic_facet |
Ross Sea |
genre |
Ross Sea |
genre_facet |
Ross Sea |
op_rights |
Assumed arXiv.org perpetual, non-exclusive license to distribute this article for submissions made before January 2004 http://arxiv.org/licenses/assumed-1991-2003/ |
op_doi |
https://doi.org/10.48550/arxiv.q-bio/0605025 |
_version_ |
1766179761869029376 |