… , have been analyzed among the traditional routing algorithms. This paper … Q learning
algorithm and suggests a hybrid QL-Feed Forward routing algorithm (QFFR) algorithm for routing …

… reinforcement learning techniques. We propose a multi-agent reinforcement learning
framework for adaptive routing in … of both the real-time Q-learning and the actor-critic methods. …

… deep reinforcement learning (DRL) model, which is composed of an actor, an adaptive critic
and a routing … The actor, based on the attention mechanism, is designed to generate routing …

… In this paper, a new optimization model based on reinforcement learning (RL) and a
complementary tree-based regression method is proposed. In our proposed model, when the RL …

… adaptive routing protocol based on reinforcement learning (ARPRL) is proposed. Through
distributed Q-Learning algorithm… The second is hybrid ad-hoc routing, which is represented by …

… Q-learning applied for selecting the route in a wireless mesh network. 4) This paper … of
reinforcement learning algorithms (eg, learning rates, discount factor) for improved self-learning …

… We observe that Algorithm 3 is the model-based reinforcement learning Full Backup Algorithm
… Fei, “MURAO: A multi-level routing protocol for acousticoptical hybrid underwater wireless …

… concept of adaptive routing with machine learning algorithms, … adaptive Reinforcement
Learning-based routing algorithm, … The hybrid multi-hop routing protocols combine the first two …

Supposing at a time step t, agent i chooses to send a packet with destination s through
outgoing link a to next agent j, we use ui t to denote the queue delay, and use vi t to denote the …

… on hybrid neural networks [24]–[30], the deep learning (DL) has been introduced in RL,
named deep reinforcement learning (… , agents can learn adaptive routing policies in unknown …