… review reinforcement learning and its characteristics and study how to use this technique for
creating routing … IV2XQ is a geographic routing scheme, which utilizes a hierarchical routing …

… It was shown that machine learning techniques have promising results in … in routing [13]. In
this paper, we evaluate how machine learning techniques can be used to address the routing …

… On the other hand, Reinforcement Learning has gained momentum as a tool … Reinforcement
Learning (DRL) to perform SFC placement on multiple domains. We devise a hierarchical …

… (QoS) routing for heavy volume IoT data transmissions this paper proposes a machine
learning-based routing algorithm with a multi-agent environment. The overall routing process is …

… MULTI-ACTION DRL FOR DJSP WITH JOB ARRIVALS In this section, a hierarchical MDRL
method is proposed to tackle the challenges associated with the dynamic DJSP. First, a …

… routing protocol based on reinforcement learning (R. L), called reinforcement learning
routing … networks (RRIN), to address the limitations of existing routing protocols. Low end-to-end …

… Reinforcement Learning (RL) has been applied to many hard problems, like Atari [24], …
learning [4]. A few studies have considered simpler versions of VRP using reinforcement learning, …

… This paper studies a dynamic vehicle routing problem under stochastic … to learn a base
policy that captures human experience for better decision making. The reinforcement learning …

… an intelligent algorithm based on reinforcement learning to improve the QoS features of
SDN… (QAR) routing method based on reinforcement learning for multi-layer hierarchical SDN. …

… This study presents a reinforcement learning routing protocol using tree-based eligibility
traces (RLR-TET). During learning, greedy action chains are created, and the various greedy …