… Abstract– Resource management problems in systems and networking often … deep
reinforcement learning for AI problems, we consider building systems that learn to manage resources …

… resource management framework does not require any prior knowledge on the network
dynamics or statistics. It can automatically learn … RL-based resource management framework as …

… the resource management consistent with users’ activities per slice. In that regard, deep
reinforcement learning … resource management for network slicing scenarios, which include radio …

… Abstract—We propose a mechanism for distributed resource management and interference
mitigation in wireless networks using multi-agent deep reinforcement learning (RL). We …

… connects reinforcement learning with deep learning to generate the (near-) optimal resource
… (SA), followed by using reinforcement learning experiences for optimization. Therefore, the …

… for resource management in network slicing and analyzes approaches using reinforcement
learning (… research directions related to RL/DRL-based network slice resource management. …

… a learning-based algorithm for efficient resource management to achieve DNN inference in
IIoT networks [35]. To rapidly obtain the optimal decisions under stochastic environment, we …

… Since this survey mainly focuses on deep reinforcement learning for RRAM in wireless
networks… /OR” combinations of them; ”deep reinforcement learning,” ”DRL,” ”resource allocation,” ”…

… • We examine the RL concept as potential solutions to the resource management issues. •
The … Section II present the key concept of fog computing and existing resource management …

… To address this issue, we introduce a resource management system for network slicing
and propose a dynamic resource adjustment algorithm based on reinforcement learning …