  In this work the system of agents is applied to establish a model of the
nonlinear distributed signal processing. The evolution of the system of the
agents - by the prediction time scale diversified trend followers, has been
studied for the stochastic time-varying environments represented by the real
currency-exchange time series. The time varying population and its statistical
characteristics have been analyzed in the non-interacting and interacting
cases. The outputs of our analysis are presented in the form of the mean
life-times, mean utilities and corresponding distributions. They show that
populations are susceptible to the strength and form of inter-agent
interaction. We believe that our results will be useful for the development of
the robust adaptive prediction systems.
