Using crude probability estimates to guide diagnosis
Artificial Intelligence
Qualitative and quantitative simulation: bridging the gap
Artificial Intelligence
Semi-Quantitative Comparative Analysis
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Qualitative simulation and related approaches for the analysis of dynamic systems
The Knowledge Engineering Review
Experiment selection for the discrimination of semi-quantitative models of dynamical systems
Artificial Intelligence
Experiment selection for the discrimination of semi-quantitative models of dynamical systems
Artificial Intelligence
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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.