Fundamentals of Bayesian Epistemology 2

Arguments, Challenges, Alternatives

Michael G. Titelbaum (Autor)

Buch | Softcover

416 Seiten

2022
Oxford University Press (Verlag)
978-0-19-286315-7 (ISBN)

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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.

Bayesian ideas have recently been applied across such diverse fields as philosophy, statistics, economics, psychology, artificial intelligence, and legal theory. Fundamentals of Bayesian Epistemology examines epistemologists' use of Bayesian probability mathematics to represent degrees of belief. Michael G. Titelbaum provides an accessible introduction to the key concepts and principles of the Bayesian formalism, enabling the reader both to follow epistemological debates and to see broader implications

Volume 1 begins by motivating the use of degrees of belief in epistemology. It then introduces, explains, and applies the five core Bayesian normative rules: Kolmogorov's three probability axioms, the Ratio Formula for conditional degrees of belief, and Conditionalization for updating attitudes over time. Finally, it discusses further normative rules (such as the Principal Principle, or indifference principles) that have been proposed to supplement or replace the core five.

Volume 2 gives arguments for the five core rules introduced in Volume 1, then considers challenges to Bayesian epistemology. It begins by detailing Bayesianism's successful applications to confirmation and decision theory. Then it describes three types of arguments for Bayesian rules, based on representation theorems, Dutch Books, and accuracy measures. Finally, it takes on objections to the Bayesian approach and alternative formalisms, including the statistical approaches of frequentism and likelihoodism.

Michael G. Titelbaum is a Vilas Distinguished Achievement Professor in the Department of Philosophy at the University of Wisconsin-Madison. After majoring in philosophy at Harvard, he had a brief career as a high school teacher. He then earned a PhD in philosophy from the University of California, Berkeley, and completed a Visiting Research Fellowship at the Australian National University. He began at UW-Madison in 2009, and was Chair of the Department of Philosophy 2019-2022.

III Applications
6: Confirmation
7: Decision Theory
IV Arguments for Bayesianism
8: Representation Theorems
9: Dutch Book Arguments
10: Accuracy Arguments
Challenges and Objections
11: Memory Loss and Self-Location
12: Old Evidence, Logical Omniscience
13: Alternatives to Bayesianism
14: Comparisons, Ranges, Dempster-Shafer

Erscheinungsdatum	29.07.2022
Verlagsort	Oxford
Sprache	englisch
Maße	156 x 235 mm
Gewicht	628 g
Themenwelt	Geisteswissenschaften ► Philosophie ► Erkenntnistheorie / Wissenschaftstheorie
	Mathematik / Informatik ► Mathematik
	Naturwissenschaften
ISBN-10	0-19-286315-0 / 0192863150
ISBN-13	978-0-19-286315-7 / 9780192863157
Zustand	Neuware