  We study the average Age of Information (AoI) in a system where physical
sources produce independent discrete-time updates that are each observed by
several sensors. We devise a model that is simple, but still capable to capture
the main tradeoffs. Two sensor scheduling policies are proposed to minimize the
AoI of the sources; one in which the system parameters are assumed known, and
one in which they are learned. Both policies are able to exploit the common
sensor information to reduce the AoI, resulting in large reductions in AoI
compared to common schedules.
