Title: Logic-Based Knowledge Representation (Mit Press Series in Logic Programming)
Publisher: Mit Pr
Publication Date: 1989
Language: English
ISBN 10: 026210038X
ISBN 13: 9780262100380
Binding: Hardcover
Condition: Good
Dust Jacket Condition: No Jacket

About this title

Synopsis

This book explores the building of expert systems using logic for knowledge representation and meta-level inference for control. It presents research done by members of the expert systems group of the Department of Artificial Intelligence in Edinburgh, often in collaboration with others, based on two hypotheses: that logic is a suitable knowledge representation language, and that an explicit representation of the control regime of the theorem prover has many advantages.

The editors introduce these hypotheses and present the arguments in their favor They then describe Socrates' a tool for the construction of expert systems that is based on these assumptions. They devote the remaining chapters to the solution of problems that arise from the restrictions imposed by Socrates's representation language and from the system's inefficiency.

The chapters dealing with the representation problem present a reified approach to temporal logic that makes it possible to use nonstandard logics without extending the system, and describe a general proof method for arbitrary modal logics. Those dealing with the efficiency problem discuss the technique of partial evaluation and its limitations, as well as another possible solution known as assertion-time inference.

Peter Jackson is a Senior Scientist in the Department of Applied Mathematics and Computer Sciences at the McDonnell Douglas Research Laboratory in St. Louis. Han Reichgelt is a Lecturer in Department of Psychology at the University of Nottingham. Frank van Harmelen is a Research Fellow in the Mathematical Reasoning Group at the University of Edinburgh.

Synopsis

The first section presents an abstract knowledge-based architecture (Socrates) which is capable of being specialized and configured for particular applications. The second reports some novel research which enlarges current theorem proving technology, and which the contributors (Dept. of Artificial Intelligence, Edinburg) feel should be incorporated

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