Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
A spectrum of definitions for temporal model-based diagnosis
Artificial Intelligence
Diagnosis of large active systems
Artificial Intelligence
On Communicating Finite-State Machines
Journal of the ACM (JACM)
Diagnosis of discrete-event systems from uncertain temporal observations
Artificial Intelligence
Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems
Discrete Event Dynamic 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
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
A bridged diagnostic method for the monitoring of polymorphic discrete-event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Diagnosis of quantized systems based on a timed discrete-eventmodel
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Model-Based Diagnosis of Discrete Event Systems with an Incomplete System Model
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Observation-Subsumption Checking in Similarity-Based Diagnosis of Discrete-Event Systems
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
| Hi-index | 0.00 |
Automated diagnosis of communicating-automaton networks (CANs) is a complex task, which is typically faced by model-based reasoning, where the behavior of the network is reconstructed based on its observation. This task may take advantage of knowledge-compilation techniques, where a large amount of reasoning is anticipated off-line (when the diagnostic process is not active), by simulating the behavior of the network and by constructing suitable data structures embedding diagnostic information. This (general-purpose) compiled knowledge is exploited on-line (when the diagnostic process becomes active), so as to generate the solution to the problem. Additional reusable (special-purpose) compiled knowledge is generated on-line when solving new problems. A software environment for the diagnosis of CANs has been developed in the C programming language with the support of the PostgreSQL relational database management system, under the Linux operating system. It supports the modeling and preprocessing of CANs as well as the solution of diagnostic problems, including on-line knowledge compilation. The environment has been tested through a variety of experiments. Results are encouraging and provide a valuable feedback for further work. Copyright © 2006 John Wiley & Sons, Ltd.