… reinforcement learning (DRL) [11] approach for the UAV to determine the optimized data
delivery and wireless … where the UAV is equipped with wireless energy transfer functionalities to …

… (MEC) under time-varying wireless channels. We propose a joint … By modeling the wireless
channel as a finite state Markov … By using deep reinforcement learning (DRL) algorithm, we …

… section, Monte Carlo and reinforcement learning simulations are done to evaluate the
proposed resource management schemes in LoRa wireless networks by averaging up to 10000 …

… reinforcement learning for energy optimization and resource allocation in wireless networks,
… AND/OR” combinations of them; ”deep reinforcement learning,” ”DRL,” ”energy optimization,…

… ABSTRACT For densely deployed wireless local area networks (WLANs), this paper proposes
a deep reinforcement learning-based channel allocation scheme that enables the efficient …

… long short-term memory network-based deep learning method for predicting the downlink …
-free reinforcement learning algorithm in wireless communication networks that combines …

… to share a common wireless spectrum and each network is unaware of the … reinforcement
learning (DRL) based MAC protocol for a particular network, and the objective of this network is …

… In this paper, a new game theory approach based on reinforcement learning to recover
Coverage Holes in a distributed way is proposed. For the formulated potential game, sensor …

… We study reinforcement learning at the sensors to find a transmission … in wireless powered
sensor networks. Numerical results demonstrate that the proposed reinforcement learning …

… communication, which uses multiagent reinforcement learning (MARL) to maximize sys…
reinforcement learning (DRL) in D2D-enabled MEC, enabling mobile users to automatically learn …