Dynamic selection of models under time constraints

The creation of an appropriate model to use for a specific task involves determining the appropriate assumptions to simplify a more complex base model. The author presents a conceptual framework for organizing a series of models that are derived with simplifying assumptions, and a decision-theoretic model-based method to determine the optimal model to select under a time constraint. He then discusses a heuristic approach to the dynamic selection of models under time constraints. He illustrates this approach by describing how it can be applied to an application to reason about physiologic abnormalities of patients in the intensive care unit (ICU) who are being treated with a mechanical breathing device (ventilator).<<ETX>>