  Inspired by the multi-head attention (MHA) mechanism in natural language
processing, this letter proposes an iterative single-head attention (ISHA)
mechanism for multi-UAV path planning. The ISHA mechanism is run by a
communication helper collecting the state embeddings of UAVs and distributing
an attention score vector to each UAV. The attention scores computed by ISHA
identify how many interactions with other UAVs should be considered in each
UAV's control decision-making. Simulation results corroborate that the
ISHA-based communication and control framework achieves faster travel with
lower inter-UAV collision risks than an MHA-aided baseline, particularly under
limited communication resources.
