  We consider a system of interacting particles with random initial conditions.
Continuum approximations of the system, based on truncations of the BBGKY
hierarchy, are described and simulated for various initial distributions and
types of interaction. Specifically, we compare the Mean Field Approximation
(MFA), the Kirkwood Superposition Approximation (KSA), and a recently developed
truncation of the BBGKY hierarchy (the Truncation Approximation - TA). We show
that KSA and TA perform more accurately than MFA in capturing approximate
distributions (histograms) obtained from Monte Carlo simulations. Furthermore,
TA is more numerically stable and less computationally expensive than KSA.
