… on deep reinforcement learning to find a risk-aware … aware decision making algorithm was
proposed to find a strategy with the minimum expected risk using deep reinforcement learning…

… Based on this framework, we propose a deep reinforcement learning-based decision
algorithm that uses a deep neural network to learning exploration strategy from the partial map. …

… of situational awareness information to future autonomous vessels. This data can also be
used for training the machine learning … of realtime situational awareness provided by the on-…

… Reinforcement Learning (DRL) approach for UAV path planning based on the global situation
… to provide the simulation environment where a situation assessment model is developed …

… demonstrates Reinforcement Learning (RL), a subset of Machine Learning (ML), to be an
effective approach for automated closed-loop guidance in these challenging regions of space. …

… The advantage of using such robots in USAR is to help reduce the workload of rescue
workers and improve their situational awareness [1]. Moreover, rescue robots can be used as …

… is a promising application area for UAV swarms [3], [6], [11], [12], which is necessary for
further activities in various domains, such as situational awareness, target tracking and attack, …

… of these algorithms: the deep reinforcement learning (DRL) techniques. We made a detailed
description of them, and we deduced the current limitations in this area. We noted that most …

… Abstract—In this paper, we propose a deep reinforcement learning (DRL)-based method
that allows unmanned aerial vehicles (UAVs) to execute navigation tasks in large-scale …

… Traditionally, there have been three major challenges in achieving situational awareness
in … Specifically, we propose a novel model-free situational awareness framework for power …