… of user rate between adjacent time slots is large. To ensure the coverage continuity, we
design a resource allocation method based on deep reinforcement learning (RDRL). Capable of …

… Considering the dynamics and continuity of task generation, we propose a deep reinforcement
learningbased dynamic resource management (DDRM) algorithm to solve the formulated …

… To ensure the coverage continuity by minimizing the rate variance of successive time slots,
we design a resource allocation method based on deep reinforcement learning (RARL). In …

… constrained resources … -Based Dynamic Resource Management (DDRM) prioritizes minimizing
long-term average delay of tasks and effectively deals with high-dimensional continuity of …

… highly dynamic and complex with very large state and action spaces, a DC-MA-DDQN algorithm
is proposed to quickly learn the optimized intelligent resource management … continuity. …

… continuity of action space, the problem is handled by normalized advantage function (NAF),
a deep reinforcement learning (… BS serves N users within its coverage. BS is equipped with …

… and the seamless continuity of services as users … High Altitude Platform Stations (HAPS)
to provide connectivity services, particularly in remote areas where traditional cellular coverage …

… of resources in cloud environments. In this thesis we propose and compare new AI solutions
(Reinforcement Learning) to orchestrate virtual resources in … The Part III is in the continuity of …

… of the proposed resource allocation using deep neural network (… number of FlyBSs, and the
coverage area of individual FlyBSs. … Note that to keep a continuity, we follow a similar system …

… advanced deep reinforcement learning algorithms to solve … which has no physical meaning
of “continuity”. For example, it … , the channel states are of high dynamics and the AoI state is …