  We consider control strategies for large-scale interacting agent systems
under uncertainty. The particular focus is on the design of robust controls
that allow to bound the variance of the controlled system over time. To this
end we consider $\mathcal{H}_\infty$ control strategies on the agent and mean
field description of the system. We show a bound on the $\mathcal{H}_\infty$
norm for a stabilizing controller independent on the number of agents.
Furthermore, we compare the new control with existing approaches to treat
uncertainty by generalized polynomial chaos expansion. Numerical results are
presented for one-dimensional and two-dimensional agent systems.
