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Table of contents (16 chapters)
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Front Matter
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Introduction: Bayesianism into the 21st Century
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Bayesianism, Causality and Networks
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Front Matter
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Bayesianism and Decision Theory
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Front Matter
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Criticisms of Bayesianism
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Front Matter
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Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Foundations of Bayesianism
Editors: David Corfield, Jon Williamson
Series Title: Applied Logic Series
DOI: https://doi.org/10.1007/978-94-017-1586-7
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 2001
Hardcover ISBN: 978-1-4020-0223-6Published: 31 December 2001
Softcover ISBN: 978-90-481-5920-8Published: 10 October 2011
eBook ISBN: 978-94-017-1586-7Published: 14 March 2013
Series ISSN: 1386-2790
Edition Number: 1
Number of Pages: XIII, 416
Number of Illustrations: 6 b/w illustrations
Topics: Philosophy of Science, Artificial Intelligence, Probability Theory and Stochastic Processes, Statistics, general, Microeconomics