  According to empirical observations, some pattern formation phenomena in
driven many-particle systems are more pronounced in the presence of a certain
noise level. We investigate this phenomenon of fluctuation-driven ordering with
a cellular automaton model of interactive motion in space and find an optimal
noise strength, while order breaks down at high(er) fluctuation levels.
Additionally, we discuss the phenomenon of noise- and drift-induced
self-organization in systems that would show disorder in the absence of
fluctuations. In the future, related studies may have applications to the
control of many-particle systems such as the efficient separation of particles.
The rather general formulation of our model in the spirit of game theory may
allow to shed some light on several different kinds of noise-induced ordering
phenomena observed in physical, chemical, biological, and socio-economic
systems (e.g., attractive and repulsive agglomeration, or segregation).
