Representing and Reasoning with Probabilistic Knowledge: A Logical Approach to Probabilities

Abstract: The author explores logical formalisms for representing and reasoning with probabilistic information, with applications to non-monotonic reasoning, probabilities, and knowledge representation.

Keywords: book review, robotics, psychology, statistics, ai, probability, reasoning, probabilistic knowledge, nonmonotonic reasoning, knowledge representation, intelligent systems, logic, inference, degrees of belief, defeasible logic, probabilities, symbolic, mathematical, artificial intelligence.

Title: Representing and Reasoning with Probabilistic Knowledge: A Logical Approach to Probabilities Author: Fahiem Bacchus Publisher: M I T Press Date Published: February 1991 ISBN: 0262023172 LOCN: QA273.B24 1990 Dewey: 519.2 20 Pages: 233 Bibliography: 132 entries Footnotes: 96 entries

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CONTENTS

Chapter 1: Introduction

Chapter 2: Propositional Probabilities

Chapter 3: Statistical Probabilities

Chapter 4: Combining Statistical and Propositional Probabilities

Chapter 5: Default Interferences from Statistical Knowledge

LIBRARY OF CONGRESS DATA

Author:        Bacchus, Fahiem.
Title:         Representing and reasoning with probabilistic
                  knowledge : a logical approach to probabilities / Fahiem
                  Bacchus.
Published:     Cambridge, Mass. : MIT Press, c1990.
Description:   233 p. : ill. ; 24 cm.
Series:        Artificial intelligence
LC Call No.:   QA273.B24 1990
Dewey No.:     519.2 20
ISBN:          0262023172
Notes:         Includes bibliographical references (p.
                  [219]-227) and index.
Subjects:      Probabilities.
               Logic, Symbolic and mathematical.
               Artificial intelligence.
Series Entry:  Artificial intelligence (Cambridge, Mass.)
Control No.:   90013555 

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