Objective bayesianism with predicate languages

Jon Williamson

pp. 341-356

in: Kent W. Staley, Jean Miller, Deborah G. Mayo (eds), Synthese 163 (3), 2008.

Abstract

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.

Cited authors

Carnap Rudolf