Objective Bayesianism imposes two norms on degrees of belief: degrees of belief should be constrained by empirical information and they should otherwise be as equivocal as possible. The origins of objective Bayesianism are explained, with the work of Jakob Bernoulli and Laplace presented at some length. A contemporary reading of the two norms is developed in detail. Then, it is shown how Bayesian nets can be used to represent objective Bayesian degrees of belief (this leads to what are now called objective Bayesian nets).
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