Drone deep reinforcement learning: A review
Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and
diversified applications. These applications belong to the civilian and the military fields. To …
diversified applications. These applications belong to the civilian and the military fields. To …
Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization
In recent years, artificial neural networks (ANNs) and deep learning have become
increasingly popular across a wide range of scientific and technical fields, including fluid …
increasingly popular across a wide range of scientific and technical fields, including fluid …
A survey on reinforcement learning in aviation applications
Reinforcement learning (RL) has emerged as a powerful tool for addressing complex
decision making problems in various domains, including aviation. This paper provides a …
decision making problems in various domains, including aviation. This paper provides a …
Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning
This paper focuses on the active flow control of a computational fluid dynamics simulation
over a range of Reynolds numbers using deep reinforcement learning (DRL). More …
over a range of Reynolds numbers using deep reinforcement learning (DRL). More …
UAV-assisted content delivery in intelligent transportation systems-joint trajectory planning and cache management
Unmanned Aerial Vehicles (UAVs) are gaining growing interests due to the paramount roles
they play, particularly these days, in enabling new services that help modernize our …
they play, particularly these days, in enabling new services that help modernize our …
Reconfigurable intelligent surface enabled vehicular communication: Joint user scheduling and passive beamforming
Given its ability to control and manipulate wireless environments, reconfigurable intelligent
surface (RIS), also known as intelligent reflecting surface (IRS), has emerged as a key …
surface (RIS), also known as intelligent reflecting surface (IRS), has emerged as a key …
A reinforcement learning-based routing algorithm for large street networks
Evacuation planning and emergency routing systems are crucial in saving lives during
disasters. Traditional emergency routing systems, despite their best efforts, often struggle to …
disasters. Traditional emergency routing systems, despite their best efforts, often struggle to …
Optimal resource allocation in sdn/nfv-enabled networks via deep reinforcement learning
Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) are two
emerging paradigms that enable the feasible and scalable deployment of Virtual Network …
emerging paradigms that enable the feasible and scalable deployment of Virtual Network …
Robust control for dynamical systems with non-gaussian noise via formal abstractions
Controllers for dynamical systems that operate in safety-critical settings must account for
stochastic disturbances. Such disturbances are often modeled as process noise in a …
stochastic disturbances. Such disturbances are often modeled as process noise in a …
Trajectory and communication design for cache-enabled UAVs in cellular networks: A deep reinforcement learning approach
In this article, we investigate the content transmission in a heavy-crowded multiple access
cellular network, whose data traffic is offloaded through the combination of edge caching …
cellular network, whose data traffic is offloaded through the combination of edge caching …