… qualitatively compare existing RL-based routing protocols. … the main characteristics of RL-based
routing protocols. The second … enables to address RL-based routing protocols from three …

… In this paper, we propose a deep reinforcement learning (DRL)-based routing optimization
on an SDN. In the proposed method, the DRL agent learns the interdependency between the …

… Reinforcement-Based (DTRB) is a delay tolerant routing … -Agent Reinforcement Learning
techniques to learn about routes in … is executed by a learning algorithm based on the distances …

… The learning is achieved by iteratively exploring the state and action … the routing policy in
a network. In particular, we define the routing problem as choosing a certain strategy to route …

… This research presents the results of a survey on RLbased routing protocols for the
VANET architecture. To select the existing protocols, at first, we have focused on whether the …

… Hence, they are unable to find optimal routing paths … a reinforcement learning routing
algorithm (RL-Routing) to solve a TE problem of SDN in terms of throughput and delay. RL-Routing …

… Then, we construct a performance evaluation framework for routing protocols. To achieve …
a reinforcement-learning-based routing protocol. Reinforcement-learning-based routing …

… for routing in SDN, called Reinforcement Learning and Software-Defined Networking for
Intelligent Routing (… Next, we provide details about the RLagent, the RL-based routing algorithm, …

… is using machine learning techniques. In this paper we try to reach this goal by applying
Multi-Agent Reinforcement Learning (MARL) that enables agents to solve routing optimization …

… of these routing protocols is to ensure a stable routing solution with … reinforcement
learning-based routing methods in FANET are surveyed and studied. Initially, reinforcement learning, …