[PDF] In Defence Of Objective Bayesianism eBook

Author : Jon Williamson
Publisher : OUP Oxford
Page : 192 pages
File Size : 37,60 MB
Release : 2010-05-13
Category : Mathematics
ISBN : 0191576131

GET BOOK

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. According to this version, objective Bayesianism is characterized by three norms: · Probability - degrees of belief should be probabilities · Calibration - they should be calibrated with evidence · Equivocation - they should otherwise equivocate between basic outcomes 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.

Author : Jon Williamson
Publisher : Oxford University Press
Page : 192 pages
File Size : 10,31 MB
Release : 2010-05-13
Category : Computers
ISBN : 0199228000

GET BOOK

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.

Author : James O Berger
Publisher : World Scientific
Page : 381 pages
File Size : 26,70 MB
Release : 2024-03-06
Category : Mathematics
ISBN : 981128492X

GET BOOK

Bayesian analysis is today understood to be an extremely powerful method of statistical analysis, as well an approach to statistics that is particularly transparent and intuitive. It is thus being extensively and increasingly utilized in virtually every area of science and society that involves analysis of data.A widespread misconception is that Bayesian analysis is a more subjective theory of statistical inference than what is now called classical statistics. This is true neither historically nor in practice. Indeed, objective Bayesian analysis dominated the statistical landscape from roughly 1780 to 1930, long before 'classical' statistics or subjective Bayesian analysis were developed. It has been a subject of intense interest to a multitude of statisticians, mathematicians, philosophers, and scientists. The book, while primarily focusing on the latest and most prominent objective Bayesian methodology, does present much of this fascinating history.The book is written for four different audiences. First, it provides an introduction to objective Bayesian inference for non-statisticians; no previous exposure to Bayesian analysis is needed. Second, the book provides an overview of the development and current state of objective Bayesian analysis and its relationship to other statistical approaches, for those with interest in the philosophy of learning from data. Third, the book presents a careful development of the particular objective Bayesian approach that we recommend, the reference prior approach. Finally, the book presents as much practical objective Bayesian methodology as possible for statisticians and scientists primarily interested in practical applications.

Author : Ali Paya
Publisher : ICAS Press
Page : 752 pages
File Size : 29,30 MB
Release : 2021-01-01
Category : Social Science
ISBN : 1907905529

GET BOOK

This book presents the first comprehensive introduction to methods and methodologies in the humanities and social sciences in general, and Islamic Studies in particular, from a critical rationalist point of view. The book aims to be a self-sufficient theoretical and practical guide to the topics that it introduces. It contains a large selection of fully worked out review activities and review questions plus topics for further discussion which are devised to assist readers to better understand the issues which are discussed in the book. Last but not least, all efforts have been made to make sure that most (if not all) of the reading materials which are recommended in the book are not only of the highest quality but also freely available on the internet.

Author : Jan Sprenger
Publisher : Oxford University Press
Page : 384 pages
File Size : 15,14 MB
Release : 2019-08-23
Category : Philosophy
ISBN : 0191652229

GET BOOK

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.

Author : James Franklin
Publisher : JHU Press
Page : 520 pages
File Size : 32,76 MB
Release : 2015-08
Category : History
ISBN : 1421418800

GET BOOK

The Science of Conjecture provides a history of rational methods of dealing with uncertainty and explores the coming to consciousness of the human understanding of risk.

Author : Luciano Floridi
Publisher : Routledge
Page : 447 pages
File Size : 29,99 MB
Release : 2016-06-17
Category : Philosophy
ISBN : 1317633490

GET BOOK

Information and communication technology occupies a central place in the modern world, with society becoming increasingly dependent on it every day. It is therefore unsurprising that it has become a growing subject area in contemporary philosophy, which relies heavily on informational concepts. The Routledge Handbook of Philosophy of Information is an outstanding reference source to the key topics and debates in this exciting subject and is the first collection of its kind. Comprising over thirty chapters by a team of international contributors the Handbook is divided into four parts: basic ideas quantitative and formal aspects natural and physical aspects human and semantic aspects. Within these sections central issues are examined, including probability, the logic of information, informational metaphysics, the philosophy of data and evidence, and the epistemic value of information. The Routledge Handbook of Philosophy of Information is essential reading for students and researchers in philosophy, computer science and communication studies.

Author : Alexander Bird
Publisher : Oxford University Press
Page : 297 pages
File Size : 44,49 MB
Release : 2022-10-06
Category : Knowledge, Theory of
ISBN : 019960665X

GET BOOK

In Knowing Science, Alexander Bird presents an epistemology of science that rejects empiricism and gives a central place to the concept of knowledge. Science aims at knowledge and progresses when it adds to the stock of knowledge. That knowledge is social knowing--it is known by thescientific community as a whole. Evidence is that from which knowledge can be obtained by inference. From this, it follows that evidence is knowledge, and is not limited to perception, nor to observation. Observation supplies evidence that is basic relative to a field of enquiry and can be highlynon-perceptual. Theoretical knowledge is typically gained by inference to the only explanation, in which competing plausible hypotheses are falsified by the evidence. In cases where not all competing hypotheses are refuted, scientific hypotheses are not known but instead possess varying degrees ofplausibility. Plausibilities in the light of the evidence are probabilities and link eliminative explanationism to Bayesian conditionalization. Bird argues that scientific realism and anti-realism as global metascientific claims should be rejected-the track record gives us only local metascientificclaims.

Author : Rolf Haenni
Publisher : Springer Science & Business Media
Page : 154 pages
File Size : 13,36 MB
Release : 2010-11-19
Category : Science
ISBN : 9400700083

GET BOOK

While probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied - perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.