… 802.11s for mesh ad hoc network extension. A jet powers a flying ad hoc network or a
reciprocating engine, and it is piloted remotely through pre-programmed flight plans. These are …

… Abstract—Reinforcement learning (RL) based flying ad-hoc network (… Dao, et al., “Routing in
flying adhoc networks: A … Lorenz, et al., “Routing in flying adhoc networks: Survey, constraints…

… Liquid state machine learning for resource allocation in a network of cache-enabled LTE-U
UAVs. In Proceedings of the GLOBECOM 2017—2017 IEEE Global Communications …

… important role in modern network infrastructure, particularly in flying ad hoc networks (FANETs) …
in the networks. Additionally, the authors of [31] studied reinforcement learning-assisted …

… a route selection scheme for 5G-based Flying Ad-hoc Networks (FANET), where RL is …
Q-learning AODV protocol) for wireless ad-hoc networks to increase lifetime of the network. …

… Compared with terrestrial networks, flying ad hoc networks (FANETs) have more flexible
nodes and communication links, so the latter can give play to their asymmetric advantages …

… With UAV scheduling and UAV-to-UAV links, a swarm of UAVs can establish flying ad
hoc networks (FANETs) to support various services like relaying and monitoring [2]. The line-of-…

… presented a fuzzy-based routing protocol called OLSR+ for flying ad hoc networks. It is an
… Also, we try to present a multi-path routing scheme using machine learning (ML) techniques …

… highly dynamic network topology in Flying Ad hoc Networks (FANETs… In this paper, a Q-learning-based
adaptive geographic … To speed up the reinforcement learning process, our routing …

… problem in flying-IoT, where a routing approach for the internet of flying vehicles using …
medium access control scheme and a reinforcement learning based routing protocol is designed …