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Uncertain Inference

Szerző
Cambridge
Kiadó: Cambridge University Press
Kiadás helye: Cambridge
Kiadás éve:
Kötés típusa: Ragasztott papírkötés
Oldalszám: 298 oldal
Sorozatcím:
Kötetszám:
Nyelv: Angol  
Méret: 25 cm x 18 cm
ISBN: 0-521-00101-3
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Előszó

Tovább

Előszó


Vissza

Fülszöveg


Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities. There have been many approaches to. the problem of uncertain inference, ranging from probability to inductive logic to nonmonotonic logic. This book seeks to provide a clear exposition of these approaches within a unified framework.
The principal market for the book will be students and professionals in philosophy, computer science, and artificial intelligence. Among the special features of the book are a chapter on evidential probability; an interpretation of probability specifically developed with an eye to inductive and uncertain inference which has not received a basic exposition before; chapters on nonmonotonic reasoning and theory replacement that concern matters rarely addressed in standard philosophical texts; and chapters on Mill's... Tovább

Fülszöveg


Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities. There have been many approaches to. the problem of uncertain inference, ranging from probability to inductive logic to nonmonotonic logic. This book seeks to provide a clear exposition of these approaches within a unified framework.
The principal market for the book will be students and professionals in philosophy, computer science, and artificial intelligence. Among the special features of the book are a chapter on evidential probability; an interpretation of probability specifically developed with an eye to inductive and uncertain inference which has not received a basic exposition before; chapters on nonmonotonic reasoning and theory replacement that concern matters rarely addressed in standard philosophical texts; and chapters on Mill's methods and statistical inference that cover material sorely lacking in the usual treatments of Al and computer science.
Henry E. Kyburg, Jr. is Burbank Professor of Philosophy and Computer Science at the University of Rochester and Research Scientist at the Institute for Human and Machine Intelligence.
Choh Man Teng is Research Associate at the Institute for Human and Machine Intelligence: Vissza
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