System dynamics is naturally expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and to make decisions upon, given their non-linearity and the important effects that the uncertainty on data may cause. In contrast with traditional numerical simulations that may only provide a likelihood of the results obtained, we propose a constraint reasoning framework that enables safe decision support despite data uncertainty. The approach is illustrated in the tuning of drug design and in an epidemiological study.
|Journal||Applied Numerical Analysis and Computational Mathematics|
|Publication status||Published - 15 Mar 2004|
- Constraint Reasoning
- Differential Equations