Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
… The “deep” portion of DRL refers to the multiple layers of neural network that replicate the …
data and significant computing power. In recent years, computing power has dramatically …
data and significant computing power. In recent years, computing power has dramatically …
Performance optimization in mobile-edge computing via deep reinforcement learning
… for computation offloading. The problem of solving an optimal computation offloading policy
… we propose a deep Q-network-based strategic computation offloading algorithm to learn the …
… we propose a deep Q-network-based strategic computation offloading algorithm to learn the …
Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning
… selected for computation offloading. The problem of solving an optimal computation offloading
pol… deep Q-network (DQN)-based strategic computation offloading algorithm to learn the …
pol… deep Q-network (DQN)-based strategic computation offloading algorithm to learn the …
Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks
… Our results show that on average the DROO algorithm achieves over 99.5 percent of the
computation rate of the existing near-optimal benchmark method [7]. Compared to the Linear …
computation rate of the existing near-optimal benchmark method [7]. Compared to the Linear …
Deep reinforcement learning based computation offloading and resource allocation for MEC
… To work out this problem, we utilize Deep Reinforcement … a Deep Q Network (DQN) which
can use a Deep Neural … propose reinforcement learning methods to find the optimal A and f. …
can use a Deep Neural … propose reinforcement learning methods to find the optimal A and f. …
Optimal computation offloading in collaborative LEO-IoT enabled MEC: A multiagent deep reinforcement learning approach
Recently, Low Earth Orbit (LEO) satellite-based Internet of Things (LEO-IoT) becomes
attractive for computation offloading in mobile-edge computing (MEC) since it can overcome …
attractive for computation offloading in mobile-edge computing (MEC) since it can overcome …
Optimal computation resource allocation in energy-efficient edge IoT systems with deep reinforcement learning
… Based on the Markov decision process and modelfree deep … computation offloading method
to implement a deep neural network that learns from interactions to solve the computation …
to implement a deep neural network that learns from interactions to solve the computation …
Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing
… can provide computation services for UEs in a vehicle edge computing network, and proposed
a DRL method to seek optimal computation offloading and resource allocation policies. …
a DRL method to seek optimal computation offloading and resource allocation policies. …
Optimization for computational offloading in multi-access edge computing: A deep reinforcement learning scheme
J Wang, H Ke, X Liu, H Wang - Computer Networks, 2022 - Elsevier
… the optimal computation … computation offloading scheme based on reinforcement learning
(RL) to address the absence of priori knowledge. The proposed scheme can learn the optimal …
(RL) to address the absence of priori knowledge. The proposed scheme can learn the optimal …
Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks
… problems with very low computational complexity. Simulation … optimal computation
performance while stabilizing all queues in the system. Besides, it induces very low computation …
performance while stabilizing all queues in the system. Besides, it induces very low computation …
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