| Document Type
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BL
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| Record Number
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961107
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| Doc. No
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b715477
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| Main Entry
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Williamson, Jon.
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| Title & Author
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In defence of objective Bayesianism /\ Jon Williamson.
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| Publication Statement
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Oxford ;New York :: Oxford University Press,, 2010.
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| Page. NO
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vi, 185 pages :: illustrations ;; 25 cm
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| ISBN
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0199228000
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: 9780199228003
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| Bibliographies/Indexes
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Includes bibliographical references (pages 173-182) and index.
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| Contents
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Objective Bayesianism outlined -- Objective Bayesian theory -- Criticisms of objective Bayesianism -- Evidence, language, and rationality -- Objective Bayesianism -- Desiderata for a theory of probability -- From Jakob Bernoulli to Edwin Jaynes -- A characterization of objective Bayesianism -- Motivation -- Beliefs and bets -- Probability -- Calibration -- Equivocation -- Radical subjectivism -- Updating -- Objective and subjective Bayesian updating -- Four kinds of incompatibility -- Criticisms of conditionalization -- A Dutch book for conditionalization? -- Conditionalization from conservativity? -- Predicate languages -- The framework -- The Probability norm -- Properties of the closer relation -- Closure -- Characterizing equivocation -- Order invariance -- Equidistance -- Objective Bayesian Nets -- Probabilistic networks -- Representing objective Bayesian probability -- Application to cancer prognosis -- Probabilistic Logic -- A formal framework for proabilistic logics -- A range of semantics -- Objective Bayesian semantics -- A calculus for the objective Bayesian semantics -- Judgement Aggregation -- Aggregating judgements -- Belief revision and merging -- Merging evidence -- From merged evidence to judgements -- Discussion -- Languages and Relativity -- Richer languages -- Language relativity -- Objectivity -- Objective Bayesianism in Perspective -- The state of play -- Statistics -- Confirmation and science -- Epistemic metaphysics.
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| Abstract
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"How strongly should you believe the various propositions that you can express?" "That is the key question facing Bayesian epistemology. Subjective Bayesians hold that it is largely (though not entirely) up to the agent as to which degrees of belief to adopt. Objective Bayesians, on the other hand, maintain that appropriate degrees of belief are largely (though not entirely) determined by the agent's evidence. This book states and defends a version of objective Bayesian epistemology." "Objective Bayesianism has been challenged on a number of different fronts. For example, some claim it is poorly motivated, or fails to handle qualitative evidence, or yields counter-intuitive degrees of belief after updating, or suffers from a failure to learn from experience. It has also been accused of being computationally intractable, susceptible to paradox, language dependent, and of not being objective enough." "Especially suitable for graduates or researchers in philosophy of science, foundations of statistics and artificial intelligence, the book argues that these criticisms can be met and that objective Bayesianism is a promising theory with an exciting agenda for further research."--BOOK JACKET.
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| Subject
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Bayesian statistical decision theory.
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| Subject
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Knowledge, Theory of.
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| Subject
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Reasoning-- Mathematical models.
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| Subject
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31.02 philosophy and theory of mathematics.
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| Subject
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31.70 probability.
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| Subject
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Bayes-Entscheidungstheorie.
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Bayesian statistical decision theory.
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Bayes-Verfahren
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Bayes-Verfahren.
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Beslutsteori-- matematisk statistik.
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épistémologie-- théorie de Bayes.
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| Subject
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Knowledge, Theory of.
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Objektivierung
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Objektivität.
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Reasoning-- Mathematical models.
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Bayesian method.
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| Subject
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Decision theory.
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| Subject
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Epistemology.
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| Dewey Classification
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519.5/42
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| LC Classification
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QA279.5.W5475 2010
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| NLM classification
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31.02bcl
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31.70bcl
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O212.8clc
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