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(2008) Synthese 163 (3).
Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objective Bayesianism to first-order logical languages. It is argued that the objective Bayesian should choose a probability function, from all those that satisfy constraints imposed by background knowledge, that is closest to a particular frequency-induced probability function which generalises the λ = 0 function of Carnap’s continuum of inductive methods.
Publication details
DOI: 10.1007/s11229-007-9298-y
Full citation:
Williamson, J. (2008). Objective bayesianism with predicate languages. Synthese 163 (3), pp. 341-356.
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