  The control and integration of distributed, multi-sensor perceptual systems
is a complex and challenging problem. The observations or opinions of different
sensors are often disparate incomparable and are usually only partial views.
Sensor information is inherently uncertain and in addition the individual
sensors may themselves be in error with respect to the system as a whole. The
successful operation of a multi-sensor system must account for this uncertainty
and provide for the aggregation of disparate information in an intelligent and
robust manner. We consider the sensors of a multi-sensor system to be members
or agents of a team, able to offer opinions and bargain in group decisions. We
will analyze the coordination and control of this structure using a theory of
team decision-making. We present some new analytic results on multi-sensor
aggregation and detail a simulation which we use to investigate our ideas. This
simulation provides a basis for the analysis of complex agent structures
cooperating in the presence of uncertainty. The results of this study are
discussed with reference to multi-sensor robot systems, distributed Al and
decision making under uncertainty.
