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.--
Download or read book Fundamentals of Bayesian Epistemology 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.
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.--
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 2022-04-14 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fundamentals of Bayesian Epistemology 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.
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.
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.
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.
Download or read book Bayesian Epistemology written by Luc Bovens and published by Oxford University Press on Demand. 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.
Download or read book The Foundations of Bayesian Epistemology written by Kenny Easwaran and published by Routledge. This book was released on 2017-09-30 with total page 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.
Download or read book Being Rational and Being Right written by Juan Comesaña and published by Oxford University Press, USA. This book was released on 2020-03-13 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Being Rational and Being Right, Juan Comesa�a argues for a cluster of theses related to the rationality of action and belief. His starting point is that rational action requires rational belief but tolerates false belief. From there, Comesa�a provides a novel account of empirical evidence according to which said evidence consists of the content of undefeated experiences. This view, which Comesa�a calls "Experientialism," differs from the two main views of empirical evidence on offer nowadays: Factualism, according to which our evidence is what we know, and Psychologism, according to which our experiences themselves are evidence. He reasons that Experientialism fares better than these rival views in explaining different features of rational belief and action. Comesa�a embeds this discussion in a Bayesian framework, and discusses in addition the problem of normative requirements, the easy knowledge problem, and how Experientialism compares to Evidentialism, Reliabilism, and Comesa�a's own (now superseded) Evidentialist Reliabilism.
Download or read book Bayes Or Bust written by John Earman and published by Bradford Books. This book was released on 1992 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh.
Download or read book Beyond Chance and Credence written by Wayne C. Myrvold and published by Oxford University Press, USA. This book was released on 2021-02-11 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beyond Chance and Credence introduces a new way of thinking of probabilities in science that combines physical and epistemic considerations. Myrvold shows that conceiving of probabilities in this way solves puzzles associated with the use of probability and statistical mechanics.
Download or read book How Reason Almost Lost Its Mind written by Paul Erickson and published by University of Chicago Press. This book was released on 2013-11-22 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the United States at the height of the Cold War, roughly between the end of World War II and the early 1980s, a new project of redefining rationality commanded the attention of sharp minds, powerful politicians, wealthy foundations, and top military brass. Its home was the human sciences—psychology, sociology, political science, and economics, among others—and its participants enlisted in an intellectual campaign to figure out what rationality should mean and how it could be deployed. How Reason Almost Lost Its Mind brings to life the people—Herbert Simon, Oskar Morgenstern, Herman Kahn, Anatol Rapoport, Thomas Schelling, and many others—and places, including the RAND Corporation, the Center for Advanced Study in the Behavioral Sciences, the Cowles Commission for Research and Economics, and the Council on Foreign Relations, that played a key role in putting forth a “Cold War rationality.” Decision makers harnessed this picture of rationality—optimizing, formal, algorithmic, and mechanical—in their quest to understand phenomena as diverse as economic transactions, biological evolution, political elections, international relations, and military strategy. The authors chronicle and illuminate what it meant to be rational in the age of nuclear brinkmanship.
Download or read book Context and Coherence written by Una Stojnić and published by Oxford University Press, USA. This book was released on 2021-02-25 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural languages are riddled with context-sensitivity, yet how do we understand one another so effortlessly? Contrary to the dominant position, this book argues that meaning is determined entirely by discourse conventions, as we draw on a broad array of subtle linguistic conventions that determine the interpretation of context-sensitive items.
Download or read book Bayesian Epistemology written by and published by . This book was released on 2007 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Core A Practical Approach to Computational Bayesian Statistics written by Jean-Michel Marin and published by Springer Science & Business Media. This book was released on 2007-05-26 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book.
