10 citations · 17 across the 12 of their papers we have counts for
12 papers
Handover Protocol Learning for LEO Satellite Networks: Access Delay and Collision Minimization
Ju-Hyung Lee, Chanyoung Park, Soohyun Park +1
This study presents a novel deep reinforcement learning (DRL)-based handover (HO) protocol, called DHO, specifically designed to address the persistent challenge of long propagatio…
Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperation
Soohyun Park, Jae Pyoung Kim, Chanyoung Park +2
For Industry 4.0 Revolution, cooperative autonomous mobility systems are widely used based on multi-agent reinforcement learning (MARL). However, the MARL-based algorithms suffer f…
Two Tales of Platoon Intelligence for Autonomous Mobility Control: Enabling Deep Learning Recipes
Soohyun Park, Haemin Lee, Chanyoung Park +3
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 U…
Multi-Agent Reinforcement Learning for Cooperative Air Transportation Services in City-Wide Autonomous Urban Air Mobility
Chanyoung Park, Gyu Seon Kim, Soohyun Park +2
The development of urban-air-mobility (UAM) is rapidly progressing with spurs, and the demand for efficient transportation management systems is a rising need due to the multifacet…
Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications
Chanyoung Park, Haemin Lee, Won Joon Yun +2
This paper proposes a novel centralized training and distributed execution (CTDE)-based multi-agent deep reinforcement learning (MADRL) method for multiple unmanned aerial vehicles…
Workload-Aware Scheduling using Markov Decision Process for Infrastructure-Assisted Learning-Based Multi-UAV Surveillance Networks
Soohyun Park, Chanyoung Park, Soyi Jung +2
In modern networking research, infrastructure-assisted unmanned autonomous vehicles (UAVs) are actively considered for real-time learning-based surveillance and aerial data-deliver…
EQuaTE: Efficient Quantum Train Engine for Dynamic Analysis via HCI-based Visual Feedback
Soohyun Park, Won Joon Yun, Chanyoung Park +4
This paper proposes an efficient quantum train engine (EQuaTE), a novel tool for quantum machine learning software which plots gradient variances to check whether our quantum neura…
Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems
Chanyoung Park, Won Joon Yun, Jae Pyoung Kim +4
This paper proposes a novel algorithm, named quantum multi-agent actor-critic networks (QMACN) for autonomously constructing a robust mobile access system employing multiple unmann…
Software Simulation and Visualization of Quantum Multi-Drone Reinforcement Learning
Chanyoung Park, Jae Pyoung Kim, Won Joon Yun +3
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 quan…
Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility
Chanyoung Park, Soohyun Park, Gyu Seon Kim +3
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. By…
Age-of-Information Aware Contents Caching and Distribution for Connected Vehicles
Soohyun Park, Chanyoung Park, Soyi Jung +2
To support rapid and accurate autonomous driving services, road environment information, which is difficult to obtain through vehicle sensors themselves, is collected and utilized…
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control
Chanyoung Park, Soohyun Park, Soyi Jung +2
This paper addresses a novel multi-agent deep reinforcement learning (MADRL)-based positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (i.e., UAVs work…