This paper presents a novel algorithm to address resource allocation and network-slicing challenges in multiaccess edge computing (MEC) networks. Network slicing divides a physical network into virtual slices, each tailored to efficiently allocate resour
The SEAC algorithm builds on the actor–critic framework in a multi-agent MDP model to address the limited information in decentralized systems. The MDP components include the state 𝑆S representing the shared environment where all agents operate, actions 𝐴𝑖Ai taken by each agent that toget...
In the AC framework, we use temporal difference estimation with the addition of baseline as the advantage function in the update gradient to improve the convergence efficiency of the algorithm. Then, we build a NOMA downlink communication scene and embed the DRL algorithm in this scene. For the...
Meanwhile, this method can only be used to address small-scale networks, since the Q-learning algorithm generally fails to handle high-dimensional state space or large state space. Cao et al. [28] proposed a deep reinforcement learning-based on-demand charging algorithm to maximize the sum of...