… ad-hoc networks such as vehicular ad-hoc networks (VANETs), robot ad-hoc networks (RANETs),
ship ad-hoc networks (SANETs), smartphone ad hoc networks (SPANs), and wireless …

… Reinforcement learning methods can be used to control both … of reinforcement learning
methods to the mobilized ad-hoc … the mobile nodes in our ad-hoc network are embedded with …

… Vehicular ad hoc networks (VANETs) are among the most investigated topics in the field
of mobile ad hoc networks (MANETs). In VANETs, vehicles transmit information in a multihop …

… In this paper, the reinforcement learning-based routing methods in FANET are surveyed …
Initially, reinforcement learning, the Markov decision process (MDP), and reinforcement learning …

… Vehicular ad hoc network (VANET) is a … , reinforcement learning (RL) plays a significant
role in developing routing algorithms for VANET. In this paper, we review reinforcement learning …

… , we use Q-Learning, a recent form of reinforcement learning algorithm, to infer network link
state information in a distributed manner. Every network node acts as a learning agent and …

… The challenge we face is the use of reinforcement learning model to characterize the
vehicular ad hoc network. In QGrid routing method, we first divide the geographical area into …

… In vehicular ad hoc networks (VANETs), the frequent change in vehicle mobility creates …
In this article, a novel machine learning architecture using deep reinforcement learning (DRL) …

… use of model-based reinforcement learning in the context of ad hoc teamwork. We introduce
a novel approach, named TEAMSTER, where we propose learning both the environment's …

Vehicular ad hoc networks (VANETs) have been attracting interest for their potential roles in …
In addition, a reinforcement learning-based algorithm is used to consider the future reward …