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

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

… In this paper, we propose to use reinforcement learning, namely Q-learning algorithm to …
-radio wireless mesh networks. In the proposed mechanism (RLBDR), reinforcement-learning is …

… This paper proposes to use reinforcement learning, and more specifically, Q-learning …
multiradio wireless mesh networks. Our distributed routing scheme, called RLBPR, uses a learning …

… the route in a wireless mesh network. 4) This … reinforcement learning algorithms (eg, learning
rates, discount factor) for improved self-learning and interacting with the underlying network …

… is the routing mechanism originally designed for star networks is not energy sensitive. In …
reinforcement learning based routing algorithm for the wide area wireless mesh IoT networks. …

… 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 …

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

… Wireless Mesh Networks is increasingly being applied widely with explosive traffic …
reinforcement learning to improve its performance. We build a reward function for the Q-Learning …

… 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, …