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

… (2) Lack of continuity; in a highly time-varying MEC system, most existing resource allocation
… a large number of UMDs they cover. With this solution, the network and computing …

… 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. …

… In this paper, first we presented a deep reinforcement learning … significant improvements in
coverage and user experience [1]. … on maximization of system loadability using continuation …

… Considering the continuity of task generation, we set a buffer … Each pico base-station has
a coverage range of 50 m and … computation offloading and resource allocation for MEC,” in …

… As the agent learns new situations, it generalizes its learning to cover all such cases and …
key performance indicators (KPIs) for service continuity, whose minimum required values are …

… 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 …

… on the optimal resource allocation within and between slices … The authors argue that to
ensure service continuity, all these … is a costly operation in highly dynamic networks such as new …

… spectral continuity or … reinforcement learning approach applied for the first time in the
literature to solve the routing, modulation format, spectrum, and core allocation problem in dynamic …

… been applied for training stages. This paper also applied the continuation power flow analysis
to … In heterogeneous networks, base stations with transmit power, coverage range, carrier …