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Knowledge Representation
     

Knowledge Representation

by Ronald J. Brachman
 

Growing interest in symbolic representation and reasoning has pushed this backstage activity into the spotlight as a clearly identifiable and technically rich subfield in artificial intelligence. This collection of extended versions of 12 papers from the First International
Conference on Principles of Knowledge Representation and Reasoning provides a snapshot of

Overview

Growing interest in symbolic representation and reasoning has pushed this backstage activity into the spotlight as a clearly identifiable and technically rich subfield in artificial intelligence. This collection of extended versions of 12 papers from the First International
Conference on Principles of Knowledge Representation and Reasoning provides a snapshot of the best current work in AI on formal methods and principles of representation and reasoning. The topics range from temporal reasoning to default reasoning to representations for natural language.Ronald J.
Brachman is Head of the Artificial Intelligence Principles Research Department at AT&T Bell
Laboratories. Hector J. Levesque and Raymond Reiter are Professors of Computer Science at the
University of Toronto.Contents: Introduction. Nonmonotonic Reasoning in the Framework of Situation
Calculus. The Computational Complexity of Abduction. Temporal Constraint Networks. Impediments to
Universal Preference-Based Default Theories. Embedding Decision-Analytic Control in a Learning
Architecture. The Substitutional Framework for Sorted Deduction: Fundamental Results on Hybrid
Reasoning. Existence Assumptions in Knowledge Representation. Hard Problems for Simple Default
Logics. The Effect of Knowledge on Belief: Conditioning, Specificity and the Lottery Paradox in
Default Reasoning. Three-Valued Nonmonotonic Formalisms and Semantics of Logic Programs. On the
Applicability of Nonmonotonic Logic to Formal Reasoning in Continuous Time. Principles of
Metareasoning.

The MIT Press

Editorial Reviews

Booknews
A sampling of the current work in artificial intelligence on formal methods and principles of symbolic representation and reasoning. The 12 chapters are extended versions of papers from an international conference in Toronto, May 1989, and comprised the May 1991 special issue of Artificial intelligence, vol. 49, no. 1-3. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Product Details

ISBN-13:
9780262521680
Publisher:
MIT Press
Publication date:
02/18/1992
Series:
Special Issues of Artificial Intelligence
Edition description:
1st MIT Press ed
Pages:
414
Product dimensions:
7.40(w) x 10.20(h) x 0.50(d)
Age Range:
18 Years

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From the Publisher

"For computational theories of high-level cognition, Knowledge
Representation
remains the only game in town." the editors

The MIT Press

Meet the Author

Ronald J. Brachman is Head of the Artificial Intelligence Principles Research Department at
AT&T Bell Laboratories.

Hector J. Levesque is Professor of Computer Science at the University of Toronto. He is the coauthor (with Gerhard Lakemeyer) of The Logic of Knowledge Bases (MIT Press,
2001) and coeditor (with Ronald J. Brachman) of Knowledge Representation and
Reasoning
(MIT Press, 1992).

Raymond Reiter is Professor and Co-Director of the Cognitive Robotics Project in the
Department of Computer Science at the University of Toronto.

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