 (Kolmogorov 1956, ch. 1, §4). Conditionalization by \(B\) restricts all possibilities to those compatible with \(B\) and renormalizes by the probability of \(B\) to ensure that unitarity holds. The domain of the second argument place of \(\Pr(\cdot \mid -)\) is restricted to \(\mathbf{A}^{\Pr}\), since the ratio \(\Pr(A\cap B)/\Pr(B)\) is not defined if \(\Pr(B) = 0\). Note that \(\Pr(\cdot\mid B)\) is a probability measure on \(\mathbf{A}\), for every proposition \(B\) in \(\mathbf{A}^{\Pr}\). Some authors take conditional probability measures \(\Pr(\cdot, \text{given } -): \mathbf{A}\times(\mathbf{A}\setminus \{\varnothing \}) \rightarrow \Re\) as primitive and define (non-conditional) probability measures in terms of them as \(\Pr(A) = \Pr(A\), given \(W)\) for all propositions \(A\) in \(\mathbf{A}\) (see Hájek 2003). Conditional probabilities are usually assumed to be Popper-Rényi measures (Popper 1955, Rényi 1955, Rényi 1970, Stalnaker 1970, Spohn 1986). Spohn (2012, 202ff) critizices Popper-Rényi measures for their lack of a complete dynamics, a feature already pointed out by Harper (1976), and for their lack of a reasonable notion of independence. Relative probabilities (Heinemann 1997, Other Internet Resources) are claimed not to suffer from these two shortcomings.