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.
General
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