… Then introduced a novel routing scheme referred to as two-hop relay selection by multi-metric
based reinforcement learning algorithm. Multi-metric considered for routing is the following…

… policy enforcement and multi-hop routing for QoS-aware LoRa … uses fast deep reinforcement
learning called Soft Actor Critic (… Then, a concurrent optimization multi-hop routing algorithm …

… related to both routing and minimizing control … Deep Reinforcement Learning (IDRL)
approach for routing, with the aim of reducing the augmented control overhead. The IDRL routing …

… This method is based on the clustering idea and hierarchical routing methods. The number
of clusters in this method is considered to be a constant value. The capacity of each cluster is …

… considering the traffic light's effect, this paper presented a fuzzy-based hierarchical routing
scheme with tuning output membership functions based on SARSA reinforcement learning. …

… routing protocols play a vital role in this regard. Recently, reinforcement learning (RL)-based
routing … by different researchers seeking to exploit the learning procedure via trial-and-error …

… design a new deep reinforcement learning model which supports the DRQR protocol to
establish EQS routes in real time … Wang, “Hierarchical routing for vehicular ad hoc networks via …

… It is well-explored that a good routing algorithm helps in achieving energy … reinforcement
learning (RL), this article presents an RL based routing algorithm for WSN, which frames routes …

… In Section II we describe the network model used, explain what is routing and how it can be
addressed with Reinforcement Learning. Next, in Section III, we introduce R2L by explaining …

… distributed Hierarchical Reinforcement Learning approach to … problem with a lightweight
hierarchical scheme that achieves … on a combination of Q-learning model schemes running (i) …