Behavioral Petri nets: A model for diagnostic knowledge representation and reasoning

Some of the most popular approaches to model-based diagnosis consist of reasoning about a model of the behavior of the system to be diagnosed by considering a set of observations about such a system and by explaining it in terms of a set of initial causes. This process has been widely modeled via logical formalisms essentially taking into account declarative aspects. In this paper, a new approach is proposed, where the diagnostic process is captured within a framework based on the formalism of Petri nets. We introduce a particular net model, called Behavioral Petri Net (BPN). We show how the formalization of the diagnostic process can be obtained in terms of reachability in a BPN and can be implemented by exploiting classical analysis techniques of Petri nets like reachability graph analysis and P-invariant computation. Advantages of the proposed methods, like suitability to parallel processing and exploitation of linear algebra techniques, are then pointed out.