  We present an algorithm for the numerical evaluation of the state-space
distribution of an Age-of-Information network. Given enough computational
resources, the evaluation can be performed to an arbitrary high precision. An
Age-of-Information network is described by a vector of natural numbers, that
track how outdated status information from various agents is. Our algorithm
yields the means to determine any moment of the corresponding stochastic
process. This can be extremely valuable for cases in which the network consists
of controllers that communicate with one another, as it potentially allows for
less conservative control behavior. It also enables the comparison of different
policies regarding their performance (minimizing the average
Age-of-Information) to a much more accurate degree than was possible before.
This is illustrated using the conventional MaxWeight policy and the optimal
policy. We also validate and compare the algorithm with
Monte-Carlo-Simulations.
