Overview
Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 442)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (7 chapters)
Keywords
About this book
Autonomous, Model-Based Diagnosis Agents surveys extended logic programming and shows how this expressive language is used to model diagnosis problems stemming from applications such as digital circuits, traffic control, integrity checking of a chemical database, alarm-correlation in cellular phone networks, diagnosis of an automatic mirror furnace, and diagnosis of communication protocols. The book reviews a bottom-up algorithm to remove contradiction from extended logic programs and substantially improves it by top-down evaluation of extended logic programs. Both algorithms are evaluated in the circuit domain including some of the ISCAS85 benchmark circuits.
This comprehensive in-depth study of concepts, architectures, and implementation of autonomous, model-based diagnosis agents will be of great value for researchers, engineers, and graduate students with a background in artificial intelligence. For practitioners, it provides three main contributions: first, it provides many examples from diverse areas such as alarm correlation in phone networks to inconsistency checking in databases; second, it describes an architecture to develop agents; and third, it describes a sophisticated and declarative implementation of the concepts and architectures introduced.
Authors and Affiliations
Bibliographic Information
Book Title: Autonomous, Model-Based Diagnosis Agents
Authors: Michael Schroeder
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/978-1-4615-5739-5
Publisher: Springer New York, NY
-
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1998
Hardcover ISBN: 978-0-7923-8142-6Published: 31 March 1998
Softcover ISBN: 978-1-4613-7629-3Published: 12 October 2012
eBook ISBN: 978-1-4615-5739-5Published: 06 December 2012
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XVIII, 143
Topics: Artificial Intelligence, Information Storage and Retrieval, Data Structures and Information Theory