no code implementations • 19 Jul 2023 • Soohyun Park, Haemin Lee, Chanyoung Park, Soyi Jung, Minseok Choi, Joongheon Kim
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.
no code implementations • 23 Dec 2022 • Chanyoung Park, Haemin Lee, Won Joon Yun, Soyi Jung, Joongheon Kim
This paper proposes a novel centralized training and distributed execution (CTDE)-based multi-agent deep reinforcement learning (MADRL) method for multiple unmanned aerial vehicles (UAVs) control in autonomous mobile access applications.
no code implementations • 2 Sep 2022 • Haemin Lee, Seok Bin Son, Won Joon Yun, Joongheon Kim, Soyi Jung, Dong Hwa Kim
One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method.
no code implementations • 27 May 2022 • Seok Bin Son, Soohyun Park, Haemin Lee, Joongheon Kim, Soyi Jung, Donghwa Kim
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.
no code implementations • 29 Dec 2021 • Haemin Lee, Sean Kwon, Soyi Jung, Joongheon Kim
In this paper, multiple delivery drones compete to offer data transfer to a single fixed-location surveillance drone.
no code implementations • 17 Oct 2021 • Hyunsoo Lee, Haemin Lee, Soyi Jung, Joongheon Kim
In keeping with the rapid development of communication technology, a new communication structure is required in a next-generation communication system.
no code implementations • 25 Jul 2021 • Haemin Lee, Soyi Jung, Joongheon Kim
The data those are produced from surveillance cameras in aerial devices such as unmanned aerial networks (UAVs) are needed to be transferred to ground stations for secure data analysis.