… to adjust its own power. The PU allocates transmit power relying on its power control scheme…
We propose an asynchronous advantage actor critic (A3C)-based power control of SU that …

… , model-free and closed-loop control agent trained using deep reinforcement learning (DRL) …
power grid. The proposed agent learns from scratch to master the power grid voltage control …

… the learned power control policy, the secondary user can intelligently adjust its transmit power
… In Section III, we develop a deep reinforcement learning algorithm for power control for the …

… Conventional power control techniques first collect instantaneous global channel state … In
this paper, we exploit deep reinforcement learning (DRL) to design a multi-agent power control …

… Assaad, “Multiagent deep reinforcement learning based power control for large energy
harvesting networks, ” in Proceedings of 17th International Symposium on Modeling and …

… Optimal online power control policies for fading EH MAC are not available in the literature, …
a centralized power control policy we build upon the recent advances in the deep learning [32]…

… This paper reviews existing works on (deep) reinforcement learning considerations in
electric power system control. The works are reviewed as they relate to electric power system …

… power control and interference coordination reinforcement … First, we describe the fixed
power allocation algorithm, which … algorithm using tabular and deep implementations of Q-learning…

… channel selection and power control optimization problem, … channel selection and/or power
control in D2D networks have … on channel selection and power control accordingly. As a …

… novel adaptive emergency control schemes using deep reinforcement learning (… power
systems. Furthermore, an open-source platform named Reinforcement Learning for Grid Control (…