  In this paper, we consider a simple linear exponential quadratic Gaussian
(LEQG) tracking problem for a multi-agent system. We study the dynamical
behaviors of the group as we vary the risk-sensitivity parameter, comparing in
particular the risk averse case to the LQG case. Then we consider the evolution
of the performance per agent as the number of agents in the system increases.
We provide some analytical as well as simulation results. In general, more
agents are beneficial only if noisy agent dynamics and/or imperfect
measurements are considered. The critical value of the risk sensitivity
parameter above which the cost becomes infinite increases with the number of
agents. In other words, for a fixed positive value of this parameter, there is
a minimum number of agents above which the cost remains finite.
