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Home > Computers > Information Technology > Information Theory > Uncertain Inference-eBook
Uncertain Inference
 
 
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Uncertain Inference
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 AI. Among the special features of the book are a chapter on evidential probability, which has not received a basic exposition before; chapters on nonmonotonic reasoning and theory replacement, 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 AI and computer science.


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Title of ebook: Uncertain Inference
ISBN: 9780511032219
Publisher: Cambridge University Press
Internet download file size: 2313 kb
Released online for download: 10-24-1997
Author of eBook: Kyburg, Jr, Henry E.
Author of eBook: Teng, Choh Man

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