A SPECTRUM OF DEFINITIONS FOR TEMPORAL MODEL-BASED DIAGNOSIS

Model-based diagnosis (MBD) tackles the problem of troubleshooting sys tems starting from a description of their structure and function (or b ehavior). Time is a fundamental dimension in MBD: the behavior of most systems is time-dependent in one way or another. Temporal MBD, howeve r, is a difficult task and indeed many simplifying assumptions have be en adopted in the various approaches in the literature. These assumpti ons concern different aspects such as the type and granularity of the temporal phenomena being modeled, the definition of diagnosis, the ont ology for time being adopted. Unlike the atemporal case, moreover, the re is no general ''theory'' of temporal MBD which can be used as a kno wledge-level characterization of the problem. In this paper we present a general characterization of temporal model-based diagnosis. We dist inguish between different temporal phenomena that can be taken into ac count in diagnosis and we introduce a modeling language which can capt ure all such phenomena. Given a suitable logical semantics for such a modeling language, we introduce a general characterization of the noti ons of diagnostic problem and explanation, showing that in the tempora l case these definitions involve different parameters. Different choic es for the parameters lead to different approaches to temporal diagnos is. we define a framework in which different dimensions for temporal m odel-based diagnosis can be analyzed at the knowledge level, pointing out which are the alternatives along each dimension and showing in whi ch cases each one of these alternatives is adequate. In the final part of the paper we show how various approaches in the literature can be classified within our framework. In this way, we propose some guidelin es to choose which approach best fits a given application problem. (C) 1998 Elsevier Science B.V. All rights reserved.