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We study a model for continuous-opinion dynamics under bounded confidence. Inparticular, we analyze the importance of the initial distribution of opinionsin determining the asymptotic configuration. Thus, we sketch the structure ofattractors of the dynamical system, by means of the numerical computation ofthe time evolution of the agents density. We show that, for a given bound ofconfidence, a consensus can be encouraged or prevented by certain initialconditions. Furthermore, a noisy perturbation is added to the system with thepurpose of modeling the free will of the agents. As a consequence, theimportance of the initial condition is partially replaced by that of thestatistical distribution of the noise. Nevertheless, we still find evidence ofthe influence of the initial state upon the final configuration for a shortrange of the bound of confidence parameter.

The role of noise and initial conditions in the asymptotic solution of a bounded confidence, continuous-opinion model