  We present modeling strategies that describe the motion and interaction of
groups of pedestrians in obscured spaces. We start off with an approach based
on balance equations in terms of measures and then we exploit the descriptive
power of a probabilistic cellular automaton model. Based on a variation of the
simple symmetric random walk on the square lattice, we test the interplay
between population size and an interpersonal attraction parameter for the
evacuation of confined and darkened spaces. We argue that information overload
and coordination costs associated with information processing in small groups
are two key processes that influence the evacuation rate. Our results show that
substantial computational resources are necessary to compensate for incomplete
information -- the more individuals in (information processing) groups the
higher the exit rate for low population size. For simple social systems, it is
likely that the individual representations are not redundant and large group
sizes ensure that this non--redundant information is actually available to a
substantial number of individuals. For complex social systems information
redundancy makes information evaluation and transfer inefficient and, as such,
group size becomes a drawback rather than a benefit. The effect of group sizes
on outgoing fluxes, evacuation times and wall effects are carefully studied
with a Monte Carlo framework accounting also for the presence of an internal
obstacle.
