  We propose a (time) multiscale method for the coarse-grained analysis of
self--propelled particle models of swarms comprising a mixture of `na\"{i}ve'
and `informed' individuals, used to address questions related to collective
motion and collective decision--making in animal groups. The method is based on
projecting the particle configuration onto a single `meta-particle' that
consists of the group elongation and the mean group velocity and position. The
collective states of the configuration can be associated with the transient and
asymptotic transport properties of the random walk followed by the
meta-particle. These properties can be accurately predicted by an
advection-diffusion equation with memory (ADEM) whose parameters are obtained
from a mean group velocity time series obtained from a single simulation run of
the individual-based model.
