… Therefore, reinforcement learning (RL) is a helpful technique to select the best routing path.
In … can optimize the performance of WSN, such as energy efficiency and QoS parameters. In …

… reinforcement learning mechanism for the Softwaredefined networking (SDN) to achieve a
universal and customizable routing … QoS-aware reward functions to implement QoS adaptive …

… behaviors of wild animals are uncertain and the smart nodes are heterogeneous and with
limited capabilities, an adaptive multipath routing is needed to meet the required QoS. Similar …

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

… Optimizing QoS routing in hierarchical ATM networks using computational intelligence
techniques. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and …

… Through analyzing technical details of link model based reinforcement learning routing …
routing algorithm, and map Ad Hoc routing decision problem to reinforcement learning routing …

… , using certain QoS requirements as the criterion for judging the path pros and cons,
reinforcement learning is applied to SDN network routing in this paper. Reinforcement learning can …

… for QoS routing and Traffic Engineering in connection oriented networks, eg MPLS networks.
Based on reinforcement learning … QoS routing algorithm based on reinforcement learning …

… an efficient quality-ofservice routing protocol in cognitive radio mobile ad hoc networks (CR-MANETs),
where a QoS route is formed by exploiting deep reinforcement learning (DRL) …

… This problem of optimising routing problem while maintaining the quality of service is
considered as an NP-Hard problem [7]. There have been tremendous works for the development of …