  For Agent Based Models, in particular the Voter Model (VM), a general
framework of aggregation is developed which exploits the symmetries of the
agent network $G$. Depending on the symmetry group $Aut_{\omega} (N)$ of the
weighted agent network, certain ensembles of agent configurations can be
interchanged without affecting the dynamical properties of the VM. These
configurations can be aggregated into the same macro state and the dynamical
process projected onto these states is, contrary to the general case, still a
Markov chain. The method facilitates the analysis of the relation between
microscopic processes and a their aggregation to a macroscopic level of
description and informs about the complexity of a system introduced by
heterogeneous interaction relations. In some cases the macro chain is solvable.
