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Selection of Perturbation Experiments for Model Discrimination

Ivayla Vatcheva, Hidde de Jong, Nicolaas J.I. Mars

When a system is described by several competing models, further information about its behavior is required to distinguish between them. One way to obtain such information is to perform suitably chosen perturbation experiments. This paper introduces a method for the selection of optimal perturbation experiments for discrimination among a set of competing dynamical models. The models are assumed to have the form of semi-quantitative differential equations. The method employs an optimization criterion based on the entropy measure of information.

Keywords: qualitative reasoning, model-based reasoning

Citation: Ivayla Vatcheva, Hidde de Jong, Nicolaas J.I. Mars: Selection of Perturbation Experiments for Model Discrimination. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.191-195.


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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.