Fundamentals of Bayesian epistemology. 2, Arguments, challenges, alternatives / Michael G. Titelbaum.

Format:

Book

Author/Creator:

Titelbaum, Michael G., author.

Series:

Oxford scholarship online.

Oxford scholarship online

Language:

English

Subjects (All):

Knowledge, Theory of.

Belief and doubt.

Probabilities.

Bayesian statistical decision theory.

Physical Description:

1 online resource (pages 194-595) : illustrations (black and white)

Edition:

First edition.

Other Title:

Arguments, challenges, alternatives

Place of Publication:

Oxford : Oxford University Press, 2022.

Summary:

'Fundamentals of Bayesian Epistemology' provides an accessible introduction to the key concepts and principles of the Bayesian formalism. Volume 2 introduces applications of Bayesianism to confirmation and decision theory, then gives a critical survey of arguments for and challenges to Bayesian epistemology.

Contents:

Cover

Fundamentals of Bayesian Epistemology 2: Arguments, Challenges, Alternatives

Copyright

Contents

Quick Reference

PART III: APPLICATIONS

6: Confirmation

6.1 Formal features of the confirmation relation

6.1.1 Confirmation is weird! The Paradox of the Ravens

6.1.2 Further adequacy conditions

6.2 Carnap's theory of confirmation

6.2.1 Confirmation as relevance

6.2.2 Finding the right function

6.3 Grue

6.4 Subjective Bayesian confirmation

6.4.1 Confirmation measures

6.4.2 Subjective Bayesian solutions to the Paradox of the Ravens

6.5 Exercises

6.6 Further reading

Notes

7: Decision Theory

7.1 Calculating expectations

7.1.1 The move to utility

7.2 Expected utility theory

7.2.1 Preference rankings and money pumps

7.2.2 Savage's expected utility

7.2.3 Jeffrey's theory

7.2.4 Risk aversion and Allais' Paradox

7.3 Causal Decision Theory

7.3.1 Newcomb's Problem

7.3.2 A causal approach

7.3.3 Responses and extensions

7.4 Exercises

7.5 Further reading

Further Reading

PART IV: ARGUMENTS FOR BAYESIANISM

8: Representation Theorems

8.1 Ramsey's four-step process

8.2 Savage's representation theorem

8.3 Representation theorems and probabilism

8.3.1 Objections to the argument

8.3.2 Reformulating the argument

8.4 Exercises

8.5 Further reading

9: Dutch Book Arguments

9.1 Dutch Books

9.1.1 Dutch Books for probabilism

9.1.2 Further Dutch Books

9.2 The Dutch Book Argument

9.2.1 Dutch Books depragmatized

9.3 Objections to Dutch Book Arguments

9.3.1 The Package Principle

9.3.2 Dutch Strategy objections

9.4 Exercises

9.5 Further reading

10: Accuracy Arguments

10.1 Accuracy as calibration

10.2 The gradational accuracy argument for probabilism

10.2.1 The Brier score.

10.2.2 Joyce's accuracy argument for probabilism

10.3 Objections to the accuracy argument for probabilism

10.3.1 The absolute-value score

10.3.2 Proper scoring rules

10.3.3 Are improper rules unacceptable?

10.4 Do we really need Finite Additivity?

10.5 An accuracy argument for Conditionalization

10.6 Exercises

10.7 Further reading

PART V: CHALLENGES AND OBJECTIONS

11: Memory Loss and Self-locating Credences

11.1 Memory loss

11.1.1 The problem

11.1.2 A possible solution

11.1.3 Suppositional Consistency

11.2 Self-locating credences

11.2.1 The problem

11.2.2 The HTM approach

11.2.3 Going forward

11.3 Exercises

11.4 Further reading

12: Old Evidence and Logical Omniscience

12.1 Old evidence

12.1.1 The problem

12.1.2 Solutions to the diachronic problem

12.1.3 Solutions to the synchronic problem

12.1.4 More radical solutions

12.2 Logical omniscience

12.2.1 Clutter avoidance and partial distributions

12.2.2 Logical confirmation and logical learning

12.2.3 Allowing logical uncertainty

12.2.4 Logical omniscience reconsidered

12.3 Exercises

12.4 Further reading

13: The Problem of the Priors and Alternatives to Bayesianism

13.1 The Problem of the Priors

13.1.1 Understanding the problem

13.1.2 Washing out of priors

13.2 Frequentism

13.2.1 Significance testing

13.2.2 Troubles with significance testing

13.3 Likelihoodism

13.3.1 Troubles with likelihoodism

13.4 Exercises

13.5 Further reading

14: Comparative Confidence, Ranged Credences, and Dempster-Shafer Theory

14.1 Comparative confidence

14.1.1 de Finetti's comparative conditions

14.1.2 The Scott Axiom

14.1.3 Extensions and challenges

14.2 Ranged credences

14.2.1 Ranged credences, representation, and evidence.

14.2.2 Extensions and challenges

14.3 Dempster-Shafer theory

14.4 Exercises

14.5 Further reading

Glossary for Volumes 1 &amp

2

Bibliography of Volumes 1 &amp

Index of Names in Volumes 1 &amp

2.

Notes:

Includes bibliographical references and index.

Description based on online resource; title from PDF title page (viewed on April 11, 2022).

This edition also issued in print: 2022.

Other Format:

Print version: Titelbaum, Michael G. Fundamentals of Bayesian Epistemology 2

ISBN:

0-19-195409-8

0-19-267784-5

OCLC:

1312166173