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Language: English
Published by Springer Netherlands, 1988
ISBN 10: 9027726892 ISBN 13: 9789027726896
Seller: Better World Books, Mishawaka, IN, U.S.A.
Condition: Good. 1988th Edition. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Language: English
Published by Cambridge University Press, GB, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Paperback. Condition: New. This Element explores the Bayesian approach to the logic and epistemology of scientific reasoning. Section 1 introduces the probability calculus as an appealing generalization of classical logic for uncertain reasoning. Section 2 explores some of the vast terrain of Bayesian epistemology. Three epistemological postulates suggested by Thomas Bayes in his seminal work guide the exploration. This section discusses modern developments and defenses of these postulates as well as some important criticisms and complications that lie in wait for the Bayesian epistemologist. Section 3 applies the formal tools and principles of the first two sections to a handful of topics in the epistemology of scientific reasoning: confirmation, explanatory reasoning, evidential diversity and robustness analysis, hypothesis competition, and Ockham's Razor.
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Language: English
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. This Element explores the Bayesian approach to the logic and epistemology of scientific reasoning. Section 1 introduces the probability calculus as an appealing generalization of classical logic for uncertain reasoning. Section 2 explores some of the vast terrain of Bayesian epistemology. Three epistemological postulates suggested by Thomas Bayes in his seminal work guide the exploration. This section discusses modern developments and defenses of these postulates as well as some important criticisms and complications that lie in wait for the Bayesian epistemologist. Section 3 applies the formal tools and principles of the first two sections to a handful of topics in the epistemology of scientific reasoning: confirmation, explanatory reasoning, evidential diversity and robustness analysis, hypothesis competition, and Ockham's Razor. Explores the Bayesian approach to the logic and epistemology of scientific reasoning. It introduces the probability calculus as an appealing generalization of classical logic for uncertain reasoning, explores Bayesian epistemology and applies the formal tools and principles to a handful of topics in the epistemology of scientific reasoning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Published by Cambridge University Press 2022-03-31, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Published by Cambridge University Press, 2022
ISBN 10: 1108714013 ISBN 13: 9781108714013
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Language: English
Published by Taylor and Francis Ltd, GB, 2026
ISBN 10: 1138647713 ISBN 13: 9781138647718
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Paperback. Condition: New. Bayesianism is the view that rational degrees of belief should follow probability theory. In this book, philosopher Kenny Easwaran defends Bayesianism as an effective normative framework when applied to all "doxastic subjects": humans, animals, artificial intelligences, groups, and even hypothetical aliens or angels.The book addresses major challenges: concerns about numerical precision and computational tractability, problems with infinitesimals and regularity, difficulties with act-state dependence, and debates over evidence. Easwaran employs measurement theory to show probabilistic representation is analogous to representing temperature - different scales (Fahrenheit/Celsius, probability/odds) can represent the same underlying non-numerical reality.Later chapters examine how beliefs should update through conditionalization, while distinguishing different sources of rational norms. Easwaran defends a notably permissive view: any probability function is internally rational, as reason alone cannot dictate privileged priors. However, "ecological rationality" explains why certain belief systems perform better in specific environments, acknowledging both Bayesianism's abstract permissiveness and practical constraints making certain credal states more successful.
Language: English
Published by Taylor and Francis Ltd, GB, 2026
ISBN 10: 1138647713 ISBN 13: 9781138647718
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condition: New. Bayesianism is the view that rational degrees of belief should follow probability theory. In this book, philosopher Kenny Easwaran defends Bayesianism as an effective normative framework when applied to all "doxastic subjects": humans, animals, artificial intelligences, groups, and even hypothetical aliens or angels.The book addresses major challenges: concerns about numerical precision and computational tractability, problems with infinitesimals and regularity, difficulties with act-state dependence, and debates over evidence. Easwaran employs measurement theory to show probabilistic representation is analogous to representing temperature - different scales (Fahrenheit/Celsius, probability/odds) can represent the same underlying non-numerical reality.Later chapters examine how beliefs should update through conditionalization, while distinguishing different sources of rational norms. Easwaran defends a notably permissive view: any probability function is internally rational, as reason alone cannot dictate privileged priors. However, "ecological rationality" explains why certain belief systems perform better in specific environments, acknowledging both Bayesianism's abstract permissiveness and practical constraints making certain credal states more successful.
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First Edition
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