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Tractable Reasoning in Artificial Intelligence [electronic resource] / by Marco Cadoli.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence ; 941Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1995Description: X, 286 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540494225
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Language restriction: Complexity of minimal reasoning -- Approximation of a logical theory -- Using complexity results for evaluating approximation techniques -- Conclusion.
In: Springer eBooksSummary: 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.
Item type: E-BOOKS
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IMSc Library Link to resource Available EBK6769

Language restriction: Complexity of minimal reasoning -- Approximation of a logical theory -- Using complexity results for evaluating approximation techniques -- Conclusion.

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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The Institute of Mathematical Sciences, Chennai, India