The Application of Deep Reinforcement Learning to Distributed Spectrum Access in Dynamic Heterogeneous Environments With Partial Observations
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2020.2984227
Abstract: This papera1 investigates deep reinforcement learning (DRL) based on a Recurrent Neural Network (RNN) for Dynamic Spectrum Access (DSA) under partial observations, referred to as a Deep Recurrent Q-Network (DRQN). Specifically, we consider a scenario… read more here.
Keywords: reinforcement learning; access; partial observations; deep reinforcement ... See more keywords