A diagnostic environment for automaton networks

Abstract

Abstract 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.