Proceedings of the Annual Meeting of the Cognitive Science Society

Capturing correct changes both locally and globally is crucial to predicting the behavior of physical systems. However, due to the nature of qualitative simulation techniques, they cannot avoid losing some information which is useful for finding precise global behavior. This paper describes how global constraints are represented and m a nipulated in current simulation systems, using a model of an internal combustion engine. The basic idea of our approach is to automatically generate additional information for maintaining global constraints during simulation so that simulation techniques can filter global behaviors with the sufficient information. This is done by automatically introducing variables and controlling their values to guide correct transitions between the behaviors. W e express this idea within the framework of Qualitative Process (QP) theory. This technique has been implemented and integrated into an existing qualitative simulation program QPE.