… DEEP REINFORCEMENT LEARNING FRAMEWORK In this section, we first … the
reinforcement learning method and several strategies adopted in our proposed resource allocation …

… In this article, we use the deep reinforcement learning algorithm to do with the ECN selection.
3) Assume that ECN w is finally assigned. After that ECN w sends a notice of reception of …

… Traditional model-based resource management approaches … We think it is desirable to
introduce a model-free approach … -free DRL approach to efficiently manage the resources at the …

… The resource allocation problem in the MEC system is formulated as a … A deep reinforcement
learning approach is applied to solve the problem. We also propose an improved deep Q-…

… Recent breakthroughs of deep reinforcement learning (DRL) in AlphaGo … resource allocation
and power management problem. The convolutional neural network, one example of deep …

… Combined with the efficient machine learning (ML) algorithm, a … the reinforcement learning
agent. This paper proposes a two-stage VNE algorithm based on deep reinforcement learning …

… dynamic approach, which is suitable for IoT with content delivery frequently. Furthermore,
we present a green resource allocation algorithm based on Deep Reinforcement Learning (…

… Conventional numerical optimization methods are inefficient to solve such a problem, … a
deep reinforcement learning (DRL) framework based on the actor-critic learning structure. In …

… Each UAV cluster head acts as an agent and autonomously allocates resources … deep
reinforcement learning (DRL)-based collaborative computation offloading and resource allocation (…

… a novel Deep Reinforcement learning based resource Allocation method with workload-time …
the current and future workloads in the resource allocation process. Specifically, an original …