 At every time \(t\) there is a matter of fact whether \(P_A\) obtains, which is determined by the dynamics of the system. However, we may not know whether or not this is the case. We therefore introduce epistemic probabilities expressing our uncertainty about whether \(P_A\) obtains: \(p(A^t)\) reflects an agent’s degree of belief in \(P_A\)’s obtaining at time \(t\). In the same way we can introduce conditional probabilities: \(p(A^t \mid B^{t_1})\) is our degree of belief in the system having \(P_A\) at \(t\) given that it had \(P_B\) at an earlier time \(t_1\), where \(B\) is also a subset of the system’s phase space. By the usual rule of conditional probability we have \(p(A^t \mid B^{t_1}) = p(A^t \amp B^{t_1}) / (p(B^{t_1})\). This can of course be generalised to more then one event: \(p(A^t \mid B_{1}^{t_1} \amp \ldots \amp B_{r}^{t_r})\) is our degree of belief in the system having \(P_A\) at \(t\) given that it had \(P_{B_1}\) at \(t_1, P_{B_2}\) at \(t_2,\ldots\), and \(P_{B_{ r}}\) at \(t_r\), where \(B_1 ,\ldots ,B_r\) are subsets of the system’s phase space (and \(r\) a natural number), and \(t_1 ,\ldots ,t_r\) are successive instants of time (i.e., \(t \gt t_1 \gt \ldots \gt t_r)\). 