ECAI 2004 Conference Paper

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Diagnosis of discrete-event systems by separation of concerns, knowledge compilation, and reuse

Gianfranco Lamperti, Marina Zanella

Model-based diagnosis of discrete-event systems (DESs) requires the reconstruction of the behavior of the system to be diagnosed, which is computationally expensive and, therefore, time-consuming. Accordingly, most approaches propose a trade-off between off-line and on-line computation: suitable knowledge, derived off-line from the model of the system, can be exploited on-line based on the actual observation. This way, a large amount of model-based reasoning is anticipated off-line, thereby making the on-line task considerably lighter. The essential novelty of this paper, which aims to support the diagnosis of asynchronous DESs, lies in the ability to exploit not only the general-purpose diagnostic knowledge compiled off-line but also the special-purpose knowledge generated on-line for the solution of previous problems, thereby pursuing processing reuse. To this end, compatibility checking is required: the solution of a new diagnostic problem can exploit the solution of another problem provided the latter subsumes the former.

Keywords: Diagnosis, Model-Based Reasoning, Knowledge Compilation, Knowledge Reuse, Discrete-Event Systems

Citation: Gianfranco Lamperti, Marina Zanella: Diagnosis of discrete-event systems by separation of concerns, knowledge compilation, and reuse. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.838-842.

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ECAI-2004 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Universitat Politècnica de València on behalf of Asociación Española de Inteligencia Artificial (AEPIA) and Associació Catalana d'Intel-ligència Artificial (ACIA).