Creating qualitative and combined models with discrete events

Combined models with discrete event and continuous components can represent a wide variety of complex systems that must be defined using many different models. In artificial intelligence, similar efforts are underway in the study of qualitative models for physics and reasoning about systems. Consequently, there is a need to bridge theory and technology in order to have a uniform language when either analyzing or reasoning about physical systems. The authors present how combined modeling and discrete event modeling within the simulation literature can be used to help formulate such a bridge. They present formalisms from systems theory as well as the DEVS formalism to demonstrate the underlying mathematical foundation for talking about complex systems. They also present a precise methodology for partitioning continuous systems into discrete event systems for the purpose of defining qualitative models from quantitative models