"Coping with uncertainty is a necessary part of ordinary life and it 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 artificial intelligence and computer science.

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