The advent of formal definitions of the simplicity of a theory has important implications for
model selection. But what is the best way to define simplicity? Forster and Sober ([1994]) …

The central problem with Bayesian philosophy of science is that it cannot take account of the
relevance of simplicity and unification to confirmation, induction, and scientific inference. The …

It is not inevitable that all propositions should have probabilities. That depends on what one
means by probability, a point to which I'll return. The claim that all propositions have …

Abstract We argue that David Lewis's principal principle implies a version of the principle of
indifference. The same is true for similar principles that need to appeal to the concept of …

I begin this paper with a problem that Clark Glymour has posed for Bayesians, involving the
discovery that some old evidence is found to support a new theory. I discuss two solutions to …

The main thrust of John Watkins's paper (Watkins, 1977) is criticism of the Bayesian
approach. The strange thing is that he never even mentions the standard arguments for the …

Following Nancy Cartwright and others, I suggest that most (if not all) theories incorporate, or
depend on, one or more idealizing assumptions. I then argue that such theories ought to be …

There is one sense in which Bayes' theorem, and its use in statistics and in scientific
inference, is clearly uncontroversial. It is an authentic, certified, theorem of the probability …

A common methodological adage holds that diverse evidence better confirms a hypothesis
than does the same amount of similar evidence. Proponents of Bayesian approaches to …

Two Bayesian approaches to choosing between statistical models are contrasted. One of
these is an approach which Bayesian statisticians regularly use for motivating the use of …