Deep Reinforcement Learning With Discrete Normalized Advantage Functions for Resource Management in Network Slicing

摘要

Network slicing promises to provision diversified services with distinct requirements in one infrastructure. Deep reinforcement learning (e.g., deep Q-learning, DQL) is assumed to be an appropriate algorithm to solve the demand-aware interslice resource m