… embedding decisions. To solve this problem, we introduce a reinforcement learning method
to virtual network embedding. … policy network based on reinforcement learning to make node …

… However, there is no intelligent algorithm to solve the security problem of … algorithm based
on reinforcement learning (RL). In the training phase, we use a policy network as a learning …

… In this paper, we combine deep reinforcement learning with … efficient algorithm for automatic
virtual network embedding. In … a new VNE algorithm based on deep reinforcement learning (…

… algorithm, which applied reinforcement learning (RL) and graph neural network (GNN) theory
to the algorithm, … neural network (GCNN) and RL algorithm. Based on a self-defined fitness …

… In reinforcement learning algorithms, the average rewards could be unstable or diverge when
a nonlinear approximator is applied [40]. To overcome these shortcomings, the experience …

… In this work, we presented the design and evaluation of an adaptive online virtual network
embedding algorithm based on deep reinforcement learning. A key feature of our design is …

… an actor-critic reinforcement learning algorithm driven by visual-semantic embedding. Our
experiments suggest that the supervision from embedding generalizes well across different …

… -layer VNE algorithm combining with reinforcement learning to solve the embedding of multi-…
2) We build a reinforcement learning model named MLRLModel with the goal of increasing …

… [5] propose the model-assisted deep reinforcement learning approach for VNF orchestration
… Q Network (DDQN)-based SFC embedding algorithm to solve the model, which solves the …

… Hence, we introduce the reinforcement learning algorithm [30] to solve this problem. As is
well known, the reinforcement learning algorithm is a method which is learned in practice and …