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Conditional Inference and Logic for Intelligent Systems: A Theory of Measure-free Conditioning - Tapa dura

 
9780444886859: Conditional Inference and Logic for Intelligent Systems: A Theory of Measure-free Conditioning

Sinopsis

This work is concerned with addressing an anomoly involving probability and logic. This includes the interpretation and evaluation of implicative statements in natural language, compatible with conditional probability. One of the chief motivations for investigating this problem has been the need to formalize rigorously the appropriate connections between conditional probabilities and the underlying production rules in expert sytems. This is accomplished through the development of a comprehensive theory of conditional events and an associated logic. The results of this effort should be of prime use in the design and evaluation of inference rules in expert systems, and also, allow for a new expansion of probability to include at the syntactic level the concept of conditioning. The monograph is intended for two audiences: AI researchers who are primarily interested in the management of uncertainty in expert systems, and mathematicians in the fields of probabilistic modeling, logic, and algebra.

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This work is concerned with addressing an anomoly involving probability and logic. This includes the interpretation and evaluation of implicative statements in natural language, compatible with conditional probability. One of the chief motivations for investigating this problem has been the need to formalize rigorously the appropriate connections between conditional probabilities and the underlying production rules in expert sytems. This is accomplished through the development of a comprehensive theory of conditional events and an associated logic. The results of this effort should be of prime use in the design and evaluation of inference rules in expert systems, and also, allow for a new expansion of probability to include at the syntactic level the concept of conditioning. The monograph is intended for two audiences: AI researchers who are primarily interested in the management of uncertainty in expert systems, and mathematicians in the fields of probabilistic modeling, logic, and algebra.

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Goodman, Irwin R., Nguyen, Hung T., Walker, Elbert A.
Publicado por North-Holland, 1991
ISBN 10: 0444886850 ISBN 13: 9780444886859
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Librería: Zubal-Books, Since 1961, Cleveland, OH, Estados Unidos de America

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Condición: Good. 296 pp., hardcover, ex library else text clean & binding tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Nº de ref. del artículo: ZB1162381

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Goodman, Irwin R.
Publicado por Elsevier Science Ltd, 1991
ISBN 10: 0444886850 ISBN 13: 9780444886859
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Librería: Buchpark, Trebbin, Alemania

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Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 41380046/202

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