… routing protocol considering the QoS (Quality of Service) parameters such as bandwidth
efficiency, link stability and power metric. The idea of learning … opinion, reinforcement learning is …

… the quality of service (QoS) and security of routing in SDN-based IoT environments. The
reward function for QoS-aware routing … A Q-learning reliable routing approach with a weighting …

… the routing decision-making process in VANETs through the technical framework of Deep
Reinforcement Learning … predict and optimize the routing strategy. This intelligent and adaptive …

… routing algorithms based on reinforcement learning. In the first algorithm, we have used a
neural network to approximate a reinforcement … Moreover, each router uses an on line learning …

… toend routing delays in CR-enabled IoT communication in order to maximize throughput. We
propose a reinforcement learningbased routing … the proper QoS solutions for varying routing …

… [6] apply Q-learning [8] to realize QoS adaptive routing in SDN by using reward function of …
reinforcement learning for routing optimization. We integrate the deep reinforcement learning …

… Internet that plays a crucial role in quality-of-service (QoS) guarantee. Traditional … reinforcement
learning (RL) based routing strategies on the performance of intradomain Internet routing…

… -constrained QoS Routing Algorithm (SAMQ) [22] is one of these approaches in which an
effort was made to present a situation-aware multi-constrained Quality of Service (QoS) routing …

… through Q-Learning Routing. Hence, this approach minimized the routing overhead and
reduced … QoS and energyaware cooperative routing is applied with RL via opponent modelling, …

… load balancing, which ultimately leads to poor quality of service (QoS). Therefore,
incorporating loadbalancing mechanism in RPL routing is essential to maintain efficient network …