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

By: Cadoli, Marco [author.]Contributor(s): SpringerLink (Online service)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 resourceISBN: 9783540494225Subject(s): Computer science | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Mathematical Logic and Formal Languages | Computation by Abstract DevicesAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online
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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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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