… reinforcement learning (DRL) for an adjustment of handover … learning solutions, we develop
an intelligent handover … so that the overall accumulated learning error is minimized and, thus…

… In this paper, we propose a multiple attributes decision handover strategy jointly … a
caching-aware intelligent handover strategy is given based on the deep reinforcement learning …

… handover and vertical handover? How do we improve the performance and efficiency of
deep reinforcement learning-based handover … The intelligent handover decision method is …

… Instead of adopting deep reinforcement learning structures (… on the road to speed up the
learning process. To that end, we … can learn and minimize the number of handovers when the …

… Cui, “Handover control in wireless systems via asynchronous multiuser deep reinforcement
learning… Xu, “QoE-driven intelligent handover for user-centric mobile satellite networks,” IEEE …

… a reinforcement learning-based approach is proposed to implement optimal vertical handover
… Numerical results demonstrate considerable improvement in overall latency and handover …

… for handover or not. It is obvious that there will be a cyclic dependency between handover
… to the number of handover candidates, although the number of handover candidates is …

… rate of call handover and specifically reserves some resources for important service
requests. … Artificial intelligence (AI) technology can intelligently manage and control the vehicle …

… intelligence, and machine learning techniques have been introduced [11]. In this paper, we
utilize deep reinforcement learning (… We assume that the handover of user n from the serving …

… handover process, which represents the willingness of a cell to admit the incoming handovers…
In this work, a reinforcement learningbased approach for parameter selection is introduced…