Foundations of Bayesianism

  • David Corfield
  • Jon Williamson

Part of the Applied Logic Series book series (APLS, volume 24)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Introduction: Bayesianism into the 21st Century

    1. Jon Williamson, David Corfield
      Pages 1-16
  3. Bayesianism, Causality and Networks

    1. Front Matter
      Pages 17-17
    2. A. Philip Dawid
      Pages 37-74
    3. Jon Williamson
      Pages 75-115
    4. Peter M. Williams
      Pages 117-134
  4. Logic, Mathematics and Bayesianism

    1. Front Matter
      Pages 135-135
    2. Colin Howson
      Pages 137-159
    3. David Corfield
      Pages 175-201
    4. J. B. Paris, A. Vencovská
      Pages 203-240
  5. Bayesianism and Decision Theory

    1. Front Matter
      Pages 261-261
    2. Richard Bradley
      Pages 263-290
    3. Edward F. Mcclennen
      Pages 291-307
    4. Philippe Mongin
      Pages 309-338
  6. Criticisms of Bayesianism

    1. Front Matter
      Pages 339-339

About this book

Introduction

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.

Keywords

Bayesian network Measure Philosophy of Science artificial intelligence intelligence learning logical reasoning objectivity probability science

Editors and affiliations

  • David Corfield
    • 1
  • Jon Williamson
    • 1
  1. 1.Department of PhilosophyKing’s CollegeLondonUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-017-1586-7
  • Copyright Information Springer Science+Business Media B.V. 2001
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-5920-8
  • Online ISBN 978-94-017-1586-7
  • Series Print ISSN 1386-2790
  • About this book