Abstract--We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i....
Ole J. Mengshoel, Mark Chavira, Keith Cascio, Scot...
Program slicing is a general, widely-used, and accepted technique applicable to different software engineering tasks including debugging, whereas model-based diagnosis is an AI te...
al Abstraction Luca Chittaro and Roberto Ranon Department of Mathematics and Computer Science, University of Udine, via delle Scienze 206, 33100 Udine, Italy ion has been advocat...
Model-based diagnosis of technical systems requires both a simulation machinery and a logic calculus. The former is responsible for the system's behavior analysis, the latter...
Abstract. Conflict-based diagnosis is a recently proposed probabilistic method for model-based diagnosis, inspired by consistencybased diagnosis, that uses a measure of data confli...
Abstract. We propose a framework for model-based diagnosis of systems with mobility and variable topologies, modelled as graph transformation systems. Generally speaking, model-bas...
Paolo Baldan, Thomas Chatain, Stefan Haar, Barbara...
This paper deals with the monitoring and diagnosis of large discrete-event systems. The problem is to determine, online, all faults and states that explain the flow of observatio...
Most approaches to model-based diagnosis describe a diagnosis for a system as a set of failing components that explains the symptoms. In order to characterize the typically very l...
In this paper we propose the use of process algebras as powerful frameworks for model-based diagnosis. In fact, they provide machinery and tools for building component-oriented mod...
This paper describes the DiKe model-based diagnosis framework, which incorporates multiple diagnosis engines, multiple user-level system description languages, a theorem prover, an...
Gerhard Fleischanderl, Thomas Havelka, Herwig Schr...