Principles of Knowledge Representation
Published on 1. June 1996
Book
Hardback
334 pages
978-1-57586-057-2 (ISBN)
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Description
The book contains a collection of eight survey papers written by some of the best researchers in foundations of knowledge representation and reasoning. It covers topics like theories of uncertainty, nonmonotonic and causal reasoning, logic programming, abduction, inductive logic programming, description logics, complexity in Artificial Intelligence, and model-based diagnosis. It thus provides an up-to-date coverage of recent approaches to some of the most challenging problems underlying knowledge representation and Artificial Intelligence in general.
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Content
Preface; 1. Non-standard theories of uncertainty in plausible reasoning Didier Dubois and Henri Prade; 2. Probabilistic foundations of reasoning with conditionals Judea Pearl and Moisés Goldszmidt; 3. Foundations of logic programming Vladimir Lifshitz; 4. Abductive theories in artificial intelligence Kurt Konolige; 5. Inductive logic programming Stefan Wrobel; 6. Reasoning in description logics Francesco M. Donini, Maurizio Lenzerini, Daniele Nardi and Andrea Schaerf; 7. Artificial Intelligence: A Computational Perspective Bernhard Nebel; 8. The Consistency-based Approach to Automated Diagnosis of Devices Oscar Dressler and Peter Struss; Index.