Lntroduction: Bayesianism into the 21st century
| Abstract | Bayesian theory now incorporates a vast body of mathematical, statistical and computational techniques that are widely applied in a panoply of disciplines, from artificial intelligence to zoology. Yet Bayesians rarely agree on the basics, even on the question of what Bayesianism actually is. This book is about the basics e about the opportunities, questions and problems that face Bayesianism today. | |||||||||
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Prasanta S. Bandyopadhyay & Gordon Brittan (2010). Two Dogmas of Strong Objective Bayesianism. International Studies in the Philosophy of Science 24 (1):45 – 65.
Jon Williamson (2011). Objective Bayesianism, Bayesian Conditionalisation and Voluntarism. Synthese 178 (1):67-85.
David Corfield & Jon Williamson (eds.) (2001). Foundations of Bayesianism. Kluwer Academic Publishers.
Darrell P. Rowbottom (2012). Objective Bayesianism Defended? Metascience 21 (1):193-196.
Jonathan Weisberg (2009). Locating IBE in the Bayesian Framework. Synthese 167 (1):125 - 143.
Kenny Easwaran (2011). Bayesianism I: Introduction and Arguments in Favor. Philosophy Compass 6 (5):312-320.
Richard Bradley (2001). Ramsey and the Measurement of Belief. In David Corfield & Jon Williamson (eds.), Foundations of Bayesianism.
Mathias Risse (2003). Bayesianism, —Quo Vadis?—Critical Notice: David Corfield and Jon Williamson (Eds.), Foundations of Bayesianism. Philosophy of Science 70 (1):225-231.
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