  The computational cost of large-scale multi-agent based simulations (MABS)
can be extremely important, especially if simulations have to be monitored for
validation purposes. In this paper, two methods, based on self-observation and
statistical survey theory, are introduced in order to optimize the computation
of observations in MABS. An empirical comparison of the computational cost of
these methods is performed on a toy problem.
