  Unmanned aerial vehicles (UAVs) can be used to localize victims, deliver
first-aid, and maintain wireless connectivity to victims and first responders
during search/rescue and public safety scenarios. In this letter, we consider
the problem of navigating a UAV to a Rayleigh fading wireless signal source,
e.g. the Internet-of-Things (IoT) devices such as smart watches and other
wearables owned by the victim in an indoor environment. The source is assumed
to transmit RF signals, and a Q-learning algorithm is used to navigate the UAV
to the vicinity of the source. Our results show that the time averaging window
and the exploration rate for the Q-learning algorithm can be optimized for
fastest navigation of the UAV to the IoT device. As a result, Q-learning
achieves the best performance with smaller convergence time overall.
