… handover strategy based on multi-agent reinforcement learning that aims to minimize average
satellite handovers … strategy outperforms the local handover strategies based on basic …

… even be a solution to reduce handovers in mobile networks since 5G … Learning (ML) techniques
to create an intelligent handover … Machine learning has become a significant intelligence …

… in mobile HetNets, leveraging modern tools from deep reinforcement learning (RL). …
Handover control in wireless systems via asynchronous multiuser deep reinforcement learning…

… -based smart handoff scheme to minimize handover cost … intelligent handoff strategy based
on reinforcement learning in … to reinforcement learning theory and propose an intelligent …

… Reinforcement Learning (DRL) based UAV Handover Decision (UHID) scheme to determine
when it is essential for UAV to execute the handover for … to dynamically learn the UHID in an …

… a machine learning method for learning the optimal time and destination for handovers in
5G radio networks, as well as how to use the learned model to trigger handovers based on the …

… following the theory of deep reinforcement learning [13]. In the … Then, the deep reinforcement
learning based handoff framework … the intelligence and the adaptability of our algorithm. …

… In this paper, we propose a multi-agent reinforcement learning approach for user association,
which can reduce signaling overhead by using only local information at each user and …

… In this paper, we consider an intelligent task offloading scenario for vehicular environments
… deep reinforcement learning with Double Q-learning which allows user equipments to learn …

… In addition, we also briefly discuss how intelligent HO schemes can help in emergency …
with similar mobility pattern then deep reinforcement learning was implemented to determine the …