Bayesianism (138 results)

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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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346 S., Ln. 1-2. Boston Studies in the Philosophy of Science,109).

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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. …

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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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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