  We study a model for continuous-opinion dynamics under bounded confidence. In
particular, we analyze the importance of the initial distribution of opinions
in determining the asymptotic configuration. Thus, we sketch the structure of
attractors of the dynamical system, by means of the numerical computation of
the time evolution of the agents density. We show that, for a given bound of
confidence, a consensus can be encouraged or prevented by certain initial
conditions. Furthermore, a noisy perturbation is added to the system with the
purpose of modeling the free will of the agents. As a consequence, the
importance of the initial condition is partially replaced by that of the
statistical distribution of the noise. Nevertheless, we still find evidence of
the influence of the initial state upon the final configuration for a short
range of the bound of confidence parameter.
