Discrimination of Semi-Quantitative Models by Experiment Selection: Method and Application in Population Biology

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Vatcheva, Ivayla and Bernard, Olivier and Jong de, Hidde and Gouze, Jean-Luc and Mars, Nicolaas J.I. (2001) Discrimination of Semi-Quantitative Models by Experiment Selection: Method and Application in Population Biology. In: International Joint Conference on Artificial Intelligence, IJCAI 2001, 4-10 August 2001, Seattle, WA.

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Abstract:Modeling an experimental system often results in a number of alternative models that are justified equally well by the experimental data. In order to discriminate between these models, additional experiments are needed. We present a method for the discrimination of models in the form of semiquantitative differential equations. The method is a generalization of previous work in model discrimination. It is based on an entropy criterion for the selection of the most informative experiment which can handle cases where the models predict multiple qualitative behaviors. The applicability of the method is demonstrated on a real-life example, the discrimination of a set of competing models of the growth of phytoplankton in a bioreactor.
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Link to this item:http://purl.utwente.nl/publications/59861
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