Uncertain Inference [Paperback]

This book presents a clear exposition of the approaches to the problem of uncertain inference.Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. 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.This book is for students and professionals in philosophy, computer science, and AI.Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. 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.This book is for students and professionals in philosophy, computer science, and AI.Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. 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.Preface; 1. Historical background; 2. First order logic; 3. The probability calculus; 4. Interpretations of probability; 5. Nonstandard measures of support; 6. Nonmonotonic reasoning; 7. Theory replacement; 8. Statistical inference; 9. Evidential probability; 10. Semantics; 11. Applications; 12. Scientific inference. Overall this book is one of lC9