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Found 16 papers, 0 papers with code
Handover Protocol Learning for LEO Satellite Networks: Access Delay and Collision Minimization
This study presents a novel deep reinforcement learning (DRL)-based handover (HO) protocol, called DHO, specifically designed to address the persistent challenge of long propagation delays in low-Earth orbit (LEO) satellite networks' HO procedures.
Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach
In the reusable rocket scenario, quantum reinforcement learning, which has reduced memory requirements due to fewer parameters, is a good solution.
Investigation of factors regarding the effects of COVID-19 pandemic on college students' depression by quantum annealer
Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies.
Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperation
To tackle these problems, a quantum MARL (QMARL) algorithm based on the concept of actor-critic network is proposed, which is beneficial in terms of scalability, to deal with the limitations in the noisy intermediate-scale quantum (NISQ) era.
Two Tales of Platoon Intelligence for Autonomous Mobility Control: Enabling Deep Learning Recipes
This paper presents the deep learning-based recent achievements to resolve the problem of autonomous mobility control and efficient resource management of autonomous vehicles and UAVs, i. e., (i) multi-agent reinforcement learning (MARL), and (ii) neural Myerson auction.
Entropy-Aware Similarity for Balanced Clustering: A Case Study with Melanoma Detection
Clustering data is an unsupervised learning approach that aims to divide a set of data points into multiple groups.
Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems
This paper proposes a novel algorithm, named quantum multi-agent actor-critic networks (QMACN) for autonomously constructing a robust mobile access system employing multiple unmanned aerial vehicles (UAVs).
Situation-Aware Deep Reinforcement Learning for Autonomous Nonlinear Mobility Control in Cyber-Physical Loitering Munition Systems
Thus, our proposed autonomous nonlinear drone mobility control algorithm utilizes situation-aware components those are implemented with a Raycast function in Unity virtual scenarios.
Software Simulation and Visualization of Quantum Multi-Drone Reinforcement Learning
Quantum machine learning (QML) has received a lot of attention according to its light training parameter numbers and speeds; and the advances of QML lead to active research on quantum multi-agent reinforcement learning (QMARL).
Multi-agent Reinforcement Learning
Quantum Machine Learning
+2
Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility
It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation.
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control
The reliable mobile access services can be achieved in following two ways, i. e., i) energy-efficient UAV operation and ii) reliable wireless communication services.
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications
In addition, we demonstrate the self-configurable stabilized detection with YOLOv3-tiny and FlowNet2-S, which are the real-time object detection network and an optical flow estimation network, respectively.
Tutorial on Course-of-Action (COA) Attack Search Methods in Computer Networks
In the literature of modern network security research, deriving effective and efficient course-of-action (COA) attach search methods are of interests in industry and academia.
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control
This paper creates a case where the UAVs with CCTV-cameras fly over the city area for flexible and reliable surveillance services.
Joint Mobile Charging and Coverage-Time Extension for Unmanned Aerial Vehicles
To overcome this, we need to characterize a new type of drones, so-called charging drones, which can deliver energy to MBS drones.
Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy
Volumetric imaging by fluorescence microscopy is often limited by anisotropic spatial resolution from inferior axial resolution compared to the lateral resolution.
