Joongheon Kim

Energy-Efficient Cluster Head Selection via Quantum Approximate Optimization

2020 · Electronics

This paper proposes an energy-efficient cluster head selection method in the wireless ad hoc network by using a hybrid quantum-classical approach. The wireless ad hoc network is divided into several clusters via cluster head selection, …

Quantum Multi-Agent Meta Reinforcement Learning

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Although quantum supremacy is yet to come, there has recently been an increasing interest in identifying the potential of quantum machine learning (QML) in the looming era of practical quantum computing. Motivated by this, in …

Quantum Multi - Agent Reinforcement Learning Software Design and Visual Simulations for Multi - Drone Mobility Control

2024

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). Existing …