Diagnosis of large active systems
Artificial Intelligence
Diagnosis of discrete-event systems from uncertain temporal observations
Artificial Intelligence
Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems
Discrete Event Dynamic Systems
Process algebras for systems diagnosis
Artificial Intelligence
Flexible diagnosis of discrete-event systems by similarity-based reasoning techniques
Artificial Intelligence
A bridged diagnostic method for the monitoring of polymorphic discrete-event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In discrete-event system monitoring, a set of candidate diagnoses is output at the reception of each observation fragment. However, when the observation is uncertain, this result may be not dependable: the sets of diagnoses, relevant to consecutive observation fragments, may be unrelated to one another, and, even worse, they may be unrelated to the actual diagnosis. To cope with this problem, the notion of monotonic monitoring is introduced, which is supported by specific constraints on the fragmentation of the uncertain observation, leading to the notion of stratification.