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Book The Foundations of Bayesian Epistemology

Download or read book The Foundations of Bayesian Epistemology written by Kenny Easwaran and published by . This book was released on 2018-06-15 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces students and researchers to the philosophical issues at play in the growing field of formal (or Bayesian) epistemology. It focuses not on how to do particular calculations but instead on the philosophical foundations at the convergence of belief and mathematical representation. Its central questions are: What is the nature of quantifying belief? What is the source of its norms? How is it reasonable to represent belief numerically? Accessible to those without any mathematical background, this book will become a much used classic in the field.

Book Fundamentals of Bayesian Epistemology 1

Download or read book Fundamentals of Bayesian Epistemology 1 written by Michael G. Titelbaum and published by Oxford University Press. This book was released on 2022 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Fundamentals of Bayesian Epistemology' provides an accessible introduction to the key concepts and principles of the Bayesian formalism. This volume introduces degrees of belief as a concept in epistemology and the rules for updating degrees of belief derived from Bayesian principles.--

Book Foundations of Bayesianism

Download or read book Foundations of Bayesianism written by D. Corfield and published by Springer Science & Business Media. This book was released on 2001-12-31 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. The upshot is a plethora of new problems and directions for Bayesians to pursue. The book will be of interest to graduate students or researchers who wish to learn more about Bayesianism than can be provided by introductory textbooks to the subject. Those involved with the applications of Bayesian reasoning will find essential discussion on the validity of Bayesianism and its limits, while philosophers and others interested in pure reasoning will find new ideas on normativity and the logic of belief.

Book Fundamentals of Bayesian Epistemology 2

Download or read book Fundamentals of Bayesian Epistemology 2 written by Michael G. Titelbaum and published by Oxford University Press. This book was released on 2022 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: '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.--

Book Fundamentals of Bayesian Epistemology 2

Download or read book Fundamentals of Bayesian Epistemology 2 written by Michael G. Titelbaum and published by . This book was released on 2022 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: '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.

Book Bayesian Philosophy of Science

Download or read book Bayesian Philosophy of Science written by Jan Sprenger and published by Oxford University Press. This book was released on 2019-08-23 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference—the leading theory of rationality in social science—with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners.

Book Bayesian Epistemology

Download or read book Bayesian Epistemology written by Luc Bovens and published by OUP Oxford. This book was released on 2004-01-08 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. Measurement of the coherence of information is a controversial matter: arguably, the more coherent a set of information is, the more confident we may be that its content is true, other things being equal. The authors offer a new treatment of coherence which respects this claim and shows its relevance to scientific theory choice. Bovens and Hartmann apply this methodology to a wide range of much discussed issues regarding evidence, testimony, scientific theories, and voting. Bayesian Epistemology is an essential tool for anyone working on probabilistic methods in philosophy, and has broad implications for many other disciplines.

Book In Defence of Objective Bayesianism

Download or read book In Defence of Objective Bayesianism written by Jon Williamson and published by Oxford University Press. This book was released on 2010-05-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.

Book The Probabilistic Foundations of Rational Learning

Download or read book The Probabilistic Foundations of Rational Learning written by Simon M. Huttegger and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book extends Bayesian epistemology to develop new approaches to general rational learning within the framework of probability theory

Book Bayesian Epistemology

Download or read book Bayesian Epistemology written by Luc Bovens and published by Oxford University Press, USA. This book was released on 2003 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models have much to offer to philosophy. We continually receive information from many sources - our senses, witnesses, scientific instruments - and assess whether to believe it. The authors provide a systematic Bayesian account of these features of reasoning.

Book FUNDAMENTALS OF BAYESIAN EPISTEMOLOGY 1

Download or read book FUNDAMENTALS OF BAYESIAN EPISTEMOLOGY 1 written by Michael G. Titelbaum and published by . This book was released on 2022 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Fundamentals of Bayesian Epistemology' provides an accessible introduction to the key concepts and principles of the Bayesian formalism. This volume introduces degrees of belief as a concept in epistemology and the rules for updating degrees of belief derived from Bayesian principles.

Book Foundations of Bayesianism

    Book Details:
  • Author : D. Corfield
  • Publisher : Springer Science & Business Media
  • Release : 2013-03-14
  • ISBN : 9401715866
  • Pages : 419 pages

Download or read book Foundations of Bayesianism written by D. Corfield and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. The volume includes important criticisms of Bayesian reasoning and gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. It will be of interest to graduate students, researchers, those involved with the applications of Bayesian reasoning, and philosophers.

Book Bayesianism and Scientific Reasoning

Download or read book Bayesianism and Scientific Reasoning written by Jonah N. Schupbach and published by Cambridge University Press. This book was released on 2022-01-31 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Accuracy and the Laws of Credence

Download or read book Accuracy and the Laws of Credence written by Richard Pettigrew and published by Oxford University Press. This book was released on 2016 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Richard Pettigrew offers an extended investigation into a particular way of justifying the rational principles that govern our credences (or degrees of belief). The main principles that he justifies are the central tenets of Bayesian epistemology, though many other related principles are discussed along the way. These are: Probabilism, the claims that credences should obey the laws of probability; the Principal Principle, which says how credences in hypotheses about the objective chances should relate to credences in other propositions; the Principle of Indifference, which says that, in the absence of evidence, we should distribute our credences equally over all possibilities we entertain; and Conditionalization, the Bayesian account of how we should plan to respond when we receive new evidence. Ultimately, then, this book is a study in the foundations of Bayesianism. To justify these principles, Pettigrew looks to decision theory. He treats an agent's credences as if they were a choice she makes between different options, gives an account of the purely epistemic utility enjoyed by different sets of credences, and then appeals to the principles of decision theory to show that, when epistemic utility is measured in this way, the credences that violate the principles listed above are ruled out as irrational. The account of epistemic utility set out here is the veritist's: the sole fundamental source of epistemic utility for credences is their accuracy. Thus, Pettigrew conducts an investigation in the version of epistemic utility theory known as accuracy-first epistemology. The book can also be read as an extended reply on behalf of the veritist to the evidentialist's objection that veritism cannot account for certain evidential principles of credal rationality, such as the Principal Principle, the Principle of Indifference, and Conditionalization.

Book Degrees of Belief

    Book Details:
  • Author : Franz Huber
  • Publisher : Springer Science & Business Media
  • Release : 2008-12-21
  • ISBN : 1402091982
  • Pages : 352 pages

Download or read book Degrees of Belief written by Franz Huber and published by Springer Science & Business Media. This book was released on 2008-12-21 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This anthology is the first book to give a balanced overview of the competing theories of degrees of belief. It also explicitly relates these debates to more traditional concerns of the philosophy of language and mind and epistemic logic.

Book Thinking About Statistics

Download or read book Thinking About Statistics written by Jun Otsuka and published by Taylor & Francis. This book was released on 2022-12-30 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simply stated, this book bridges the gap between statistics and philosophy. It does this by delineating the conceptual cores of various statistical methodologies (Bayesian/frequentist statistics, model selection, machine learning, causal inference, etc.) and drawing out their philosophical implications. Portraying statistical inference as an epistemic endeavor to justify hypotheses about a probabilistic model of a given empirical problem, the book explains the role of ontological, semantic, and epistemological assumptions that make such inductive inference possible. From this perspective, various statistical methodologies are characterized by their epistemological nature: Bayesian statistics by internalist epistemology, classical statistics by externalist epistemology, model selection by pragmatist epistemology, and deep learning by virtue epistemology. Another highlight of the book is its analysis of the ontological assumptions that underpin statistical reasoning, such as the uniformity of nature, natural kinds, real patterns, possible worlds, causal structures, etc. Moreover, recent developments in deep learning indicate that machines are carving out their own "ontology" (representations) from data, and better understanding this—a key objective of the book—is crucial for improving these machines’ performance and intelligibility. Key Features Without assuming any prior knowledge of statistics, discusses philosophical aspects of traditional as well as cutting-edge statistical methodologies. Draws parallels between various methods of statistics and philosophical epistemology, revealing previously ignored connections between the two disciplines. Written for students, researchers, and professionals in a wide range of fields, including philosophy, biology, medicine, statistics and other social sciences, and business. Originally published in Japanese with widespread success, has been translated into English by the author.

Book The Probabilistic Foundations of Rational Learning

Download or read book The Probabilistic Foundations of Rational Learning written by Simon M. Huttegger and published by Cambridge University Press. This book was released on 2019-12-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to Bayesian epistemology, rational learning from experience is consistent learning, that is learning should incorporate new information consistently into one's old system of beliefs. Simon M. Huttegger argues that this core idea can be transferred to situations where the learner's informational inputs are much more limited than Bayesianism assumes, thereby significantly expanding the reach of a Bayesian type of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along the way, Huttegger addresses a number of debates in epistemology and the philosophy of science, including the status of prior probabilities, whether Bayes' rule is the only legitimate form of learning from experience, and whether rational agents can have sustained disagreements. His book will be of interest to students and scholars of epistemology, of game and decision theory, and of cognitive, economic, and computer sciences.