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Tractable reasoning in artificial intelligence / Marco Cadoli.

By: Material type: TextTextSeries: Lecture notes in computer science. Lecture notes in artificial intelligence ; ; 941.Publication details: Berlin ; New York : Springer-Verlag, ©1995.Description: 1 online resource (xiv, 247 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540494225
  • 3540494227
  • 0387600582
  • 9780387600581
Subject(s): Additional physical formats: Print version:: Tractable reasoning in artificial intelligence.DDC classification:
  • 006.3/3 20
LOC classification:
  • Q335 .C23 1995
Other classification:
  • 54.72
Online resources:
Contents:
1. Introduction -- 2. Language restriction: Complexity of minimal reasoning -- 3. Approximation of a logical theory -- 4. Using complexity results for evaluating approximation techniques -- 5. Conclusions -- A Appendix to Chapter 2 -- B Appendix to Chapter 3 -- C Appendix to Chapter 4.
Action note:
  • digitized 2010 HathiTrust Digital Library committed to preserve
Summary: Logic is one of the most popular approaches to artificial intelligence. A potential obstacle to the use of logic is its high computational complexity, as logical inference is an extraordinarily powerful computational device. This book is concerned with computational aspects of the logical approach to AI. The focus is on two strategies for achieving computational tractability in knowledge representation and reasoning by language restriction and approximation. Several formalisms for knowledge representation are taken into account; among the computational problems studied are checking satisfiability and entailment of formulae, finding a model, and approximating and compiling a logical for.
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Includes bibliographical references (pages 227-239) and index.

1. Introduction -- 2. Language restriction: Complexity of minimal reasoning -- 3. Approximation of a logical theory -- 4. Using complexity results for evaluating approximation techniques -- 5. Conclusions -- A Appendix to Chapter 2 -- B Appendix to Chapter 3 -- C Appendix to Chapter 4.

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Print version record.

Logic is one of the most popular approaches to artificial intelligence. A potential obstacle to the use of logic is its high computational complexity, as logical inference is an extraordinarily powerful computational device. This book is concerned with computational aspects of the logical approach to AI. The focus is on two strategies for achieving computational tractability in knowledge representation and reasoning by language restriction and approximation. Several formalisms for knowledge representation are taken into account; among the computational problems studied are checking satisfiability and entailment of formulae, finding a model, and approximating and compiling a logical for.

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