Autonomous, Model-Based Diagnosis Agents defines and describes the implementation of an architecture for autonomous, model-based diagnosis agents. It does this by developing a logic programming approach for model-based diagnosis and introducing strategies to deal with more complex diagnosis problems...

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1. Verfasser:	Schroeder, Michael (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Boston, MA Springer US 1998
Schriftenreihe:	The Springer International Series in Engineering and Computer Science 442
Schlagworte:	Computer Science Artificial Intelligence (incl. Robotics) Information Storage and Retrieval Data Structures, Cryptology and Information Theory Computer science Data structures (Computer science) Information storage and retrieval Artificial intelligence Agent > Künstliche Intelligenz Hochschulschrift
Online-Zugang:	BTU01 URL des Erstveröffentlichers
Zusammenfassung:	Autonomous, Model-Based Diagnosis Agents defines and describes the implementation of an architecture for autonomous, model-based diagnosis agents. It does this by developing a logic programming approach for model-based diagnosis and introducing strategies to deal with more complex diagnosis problems, and then embedding the diagnosis framework into the agent architecture of vivid agents. 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
Beschreibung:	1 Online-Ressource (XVIII, 143 p)
ISBN:	9781461557395
DOI:	10.1007/978-1-4615-5739-5