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Reasoning about Uncertainty

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ISBN-10: 0262582597

ISBN-13: 9780262582599

Edition: 2005

Authors: Joseph Y. Halpern

List price: $51.00
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Description:

Uncertainty is a fundamental and unavoidable feature of daily life; in order to deal with uncertaintly intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty; the material is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics. Halpern begins…    
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Book details

List price: $51.00
Copyright year: 2005
Publisher: MIT Press
Publication date: 8/12/2005
Binding: Paperback
Pages: 456
Size: 7.25" wide x 9.25" long x 1.25" tall
Weight: 1.782
Language: English

Joseph Y. Halpern is Professor of Computer Science at Cornell University.

Preface
Introduction and Overview
Some Puzzles and Problems
An Overview of the Book
Notes
Representing Uncertainty
Possible Worlds
Probability Measures
Justifying Probability
Lower and Upper Probabilities
Dempster-Shafer Belief Functions
Possibility Measures
Ranking Functions
Relative Likelihood
Plausibility Measures
Choosing a Representation
Exercises
Notes
Updating Beliefs
Updating Knowledge
Probabilistic Conditioning
Justifying Probabilistic Conditioning
Bayes' Rule
Conditioning with Sets of Probabilities
Evidence
Conditioning Inner and Outer Measures
Conditioning Belief Functions
Conditioning Possibility Measures
Conditioning Ranking Functions
Conditioning Plausibility Measures
Constructing Conditional Plausibility Measures
Algebraic Conditional Plausibility Spaces
Jeffrey's Rule
Relative Entropy
Exercises
Notes
Independence and Bayesian Networks
Probabilistic Independence
Probabilistic Conditional Independence
Independence for Plausibility Measures
Random Variables
Bayesian Networks
Qualitative Bayesian Networks
Quantitative Bayesian Networks
Independencies in Bayesian Networks
Plausibilistic Bayesian Networks
Exercises
Notes
Expectation
Expectation for Probability Measures
Expectation for Other Notions of Likelihood
Expectation for Sets of Probability Measures
Expectation for Belief Function
Inner and Outer Expectation
Expectation for Possibility Measures and Ranking Functions
Plausibilistic Expectation
Decision Theory
The Basic Framework
Decision Rules
Generalized Expected Utility
Conditional Expectation
Exercises
Notes
Multi-Agent Systems
Epistemic Frames
Probability Frames
Multi-Agent Systems
From Probability on Runs to Probability Assignments
Markovian Systems
Protocols
Using Protocols to Specify Situations
A Listener-Teller Protocol
The Second-Ace Puzzle
The Monty Hall Puzzle
When Conditioning Is Appropriate
Non-SDP Systems
Plausibility Systems
Exercises
Notes
Logics for Reasoning about Uncertainty
Propositional Logic
Modal Epistemic Logic
Syntax and Semantics
Properties of Knowledge
Axiomatizing Knowledge
A Digression: The Role of Syntax
Reasoning about Probability: The Measurable Case
Reasoning about Other Quantitative Representations of Likelihood
Reasoning about Relative Likelihood
Reasoning about Knowledge and Probability
Reasoning about Independence
Reasoning about Expectation
Syntax and Semantics
Expressive Power
Axiomatizations
Exercises
Notes
Beliefs, Defaults, and Counterfactuals
Belief
Knowledge and Belief
Characterizing Default Reasoning
Semantics for Defaults
Probabilistic Semantics
Using Possibility Measures, Ranking Functions, and Preference Orders
Using Plausibility Measures
Beyond System P
Conditional Logic
Reasoning about Counterfactuals
Combining Probability and Counterfactuals
Exercises
Notes
Belief Revision
The Circuit-Diagnosis Problem
Belief-Change Systems
Belief Revision
Belief Revision and Conditional Logic
Epistemic States and Iterated Revision
Markovian Belief Revision
Exercises
Notes
First-Order Modal Logic
First-Order Logic
First-Order Reasoning about Knowledge
First-Order Reasoning about Probability
First-Order Conditional Logic
Exercises
Notes
From Statistics to Beliefs
Reference Classes
The Random-Worlds Approach
Properties of Random Worlds
Random Worlds and Default Reasoning
Random Worlds and Maximum Entropy
Problems with the Random-Worlds Approach
Exercises
Notes
Final Words
Notes
References
Glossary of Symbols