… Learning algorithm Q-learning applied for selecting the route in a wireless mesh network. 4)
… of reinforcement learning algorithms (eg, learning rates, discount factor) for improved self-…

… reinforcement learning, namely Q-learning algorithm to route traffic in multi-hop and multi-radio
wireless mesh networks… In the proposed mechanism (RLBDR), reinforcement-learning is …

… wireless mesh networks (WMNs) where each mesh router (MR) is equipped with multiple
radio … new routing scheme, called RLBPR (Reinforcement Learning-based Best Path Routing), …

… emerging Deep Reinforcement Learning (DRL) on communication flow control in WMNs.
Moreover, different from a general DRL based networking solution, in which the network prop…

… Wireless mesh networks (WMN) are often considered as non-scalable as they likely suffer
from interferences [1, 2]. However, this may not be the case for applications such as soil …

… Wireless mesh networks (WMNs) have been extensively studied for nearly two decades
as … , high-coverage wireless networks of the future. However, consumer demand for such …

… As a consequence, more intelligent and adaptive mesh networking solutions are needed to
… we propose a reinforcement learning-based routing framework that allows each mesh device …

… routing algorithm in this paper for WMN with heavy traffic load using reinforcement learning
… We build a reward function for the Q-Learning algorithm to choose a route so that the packet …

… Here, we evaluate the proposed wireless mesh networking framework. Starting with the
QoE-aware reinforcement learning routing and the differentiated packet scheduler, we perform …

… types of wireless networks, and covered almost every aspect of wireless communications [5],
[6… In this paper, we focus our emphasis on the cognitive wireless mesh networking scenario, …