  Scheduling of the transmission of status updates over an error-prone
communication channel is studied in order to minimize the long-term average age
of information (AoI) at the destination, under an average resource constraint
at the source node, which limits the average number of transmissions. After
each transmission, the source receives an instantaneous ACK/NACK feedback, and
decides on the next update, without a priori knowledge on the success of the
future transmissions. The optimal scheduling policy is studied under different
feedback mechanisms; in particular, standard automatic repeat request (ARQ) and
hybrid ARQ (HARQ) protocols are considered. Average-cost reinforcement learning
algorithms are proposed when the error probabilities for the HARQ system are
unknown.
