This paper faces the task of distributed diagnosis without exploiting any component behavioral model. A diagnosis problem is specified by an observation that just states whether each system output is either correct or incorrect. The system is split into parts, and a distinct diagnoser, which is supplied with knowledge that has been compiled off-line and is capable of communicating with its neighbors, is assigned to each of them. A family of methods is proposed to compute local and global minimal diagnoses that are consistent with both the observation and the system description, the latter being a kind of control flow structure.
How to Cite
consistency-based diagnosis, distributed diagnosis
(Borrego et al., 2009) D. Borrego, R.M. Gasca, M.T. Go ́mez Lo ́pez, and I. Barba. Choreography analysis for diagnosing faulty activities in business- to-business collaboration. In 20th International Workshop on Principles of Diagnosis – DX’09, pages 171–178, Stockholm, S, 2009.
(Davis, 1984) R. Davis. Diagnostic reasoning based on structure and behavior. Artificial Intelligence, 24(1):347–410, 1984.
(de Kleer and Williams, 1987) J. de Kleer and B.C. Williams. Diagnosing multiple faults. Artificial Intelligence, 32(1):97–130, 1987.
(Fowler, 2004) M. Fowler. UML Distilled: a brief guide to the standard object modeling language. Addison-Wesley, 2004.
(Reiter, 1987) R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32(1):57–95, 1987.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.