Repository | Journal | Volume | Articles
(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.
This document is unfortunately not available for download at the moment.