… Finally, reinforcement learning is a technique inspired by the … focuses on reinforcement
learning (RL) application to routing in … may result in serious fluctuation in routing performance. …

… We evaluate the performance of RL-Routing on three well-known network topologies, Fat-tree,
NSF Network (NSFNet), and Advanced Research Projects Agency Network (ARPANet) as …

… Using this knowledge when making routing decisions can lead to better routing performance.
In general, parsing and learning the collected topology information is the core problem of …

… reinforcement learning method for solving the global routing … method is deep reinforcement
learning that enables an agent … router performance lies in the change of edge capacity when …

… and Software-Defined Networking Intelligent Routing (RSIR). … a routing algorithm based
on Reinforcement Learning (RL) that takes into account link-state information to make routing …

… features in RL-based routing, and how various routing challenges and problems have been
… RL-based routing scheme. Subsequently, we present performance enhancements achieved …

… model and perform the learning process of DRL using the network model in an offline … of
DRL to improve the routing performance. • We evaluate the routing performance of the proposed …

… performance of the proposed routing technique RL-SDWSN in terms of lifetime and PDR.
The performance of RL-SDWSN is compared with previous protocols, such as Q-routing, RLBR…

… On routing and delta routing: A taxonomy and performance comparison of techniques for
packet-switched networks. IEEE Transactions on Communications, COM-24(1):43-59, January …

… is any difference whatsoever between the performance of Q-routing and shortest paths
routing at low load, as is visible in Figure 4. However, a close look at the algorithm reveals that Q-…