Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields,
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …

In this article, we study the problem of air-to-ground ultra-reliable and low-latency
communication (URLLC) for a moving ground user. This is done by controlling multiple …

We investigate the use of artificial intelligence (AI)-based techniques in learning to play a 2-
player, real-time strategy (RTS) game called Hunting-of-the-Plark. The game is challenging …

Deep convolutional neural networks (DCNNs) have enjoyed much success in many
applications, such as computer vision, automated medical diagnosis, autonomous systems …

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 …

Real-time strategy games present a significant challenge for artificial game-playing agents
by combining several fundamental AI problems. Despite the difficulties, attempts to create …

강화 학습 기술은 많은 분야에서 매우 적극적으로 활용되는 기계 학습 기술 중의 하나이며 최근
이를 사용한 많은 연구 결과를 다양한 기관에서 활발하게 보여주고 있다. 본 고에서는 이러한 …

In recent years, point clouds have attracted increasing attention in a variety of industries,
such as autonomous driving and augmented reality. The point clouds offer a denser and …

Games have become a popular testbed for Artificial Intelligence, providing a unique
environment for researchers to develop and test new AI algorithms. Among these, Deep …

Reinforcement learning (RL) methods have shown great potential in solving challenging
tasks in complex environments. It has demonstrated great success in games, with RL agents …