Published online by Cambridge University Press: 01 April 2022
The inductive reliability of Bayesian methods is explored. The first result presented shows that for any solvable inductive problem of a general type, there exists a subjective prior which yields a Bayesian inductive method that solves the problem, although not all subjective priors give rise to a successful inductive method for the problem. The second result shows that the same does not hold for computationally bounded agents, so that Bayesianism is “inductively incomplete” for such agents. Finally a consistency proof shows that inductive agents do not need to disregard inductive failure on sets of subjective probability 0 in order to be ideally rational. Together the results reveal the inadequacy of the subjective Bayesian norms for scientific methodology.
Kevin Kelly and Teddy Seidenfeld provided helpful suggestions for the construction of the proof of Theorem 1. Many helpful discussions with Kevin Kelly related to all of the issues treated in the paper, especially the material on dominance and the axioms of rational preference. Clark Glymour and Kevin Kelly read earlier drafts of the paper and made many helpful suggestions for improvement.
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