no code implementations • 17 May 2023 • Shulu Chen, Antony Evans, Marc Brittain, Peng Wei
By using DCB to precondition traffic to proper density levels, we show that reinforcement learning can achieve much better performance for tactical safety separation.
no code implementations • 1 Dec 2022 • Cooper Cone, Michael Owen, Luis Alvarez, Marc Brittain
The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport category aircraft.
no code implementations • 9 Jun 2022 • Marc Brittain, Luis E. Alvarez, Kara Breeden, Ian Jessen
We introduce AAM-Gym, a research and development testbed for Advanced Air Mobility (AAM).
no code implementations • 5 May 2021 • Wei Guo, Marc Brittain, Peng Wei
We demonstrate the effectiveness of the two sub-modules in an open-source air traffic simulator with challenging environment settings.
no code implementations • 17 Mar 2020 • Marc Brittain, Xuxi Yang, Peng Wei
A novel deep multi-agent reinforcement learning framework is proposed to identify and resolve conflicts among a variable number of aircraft in a high-density, stochastic, and dynamic sector.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 25 May 2019 • Marc Brittain, Josh Bertram, Xuxi Yang, Peng Wei
Experience replay is widely used in deep reinforcement learning algorithms and allows agents to remember and learn from experiences from the past.
no code implementations • 2 May 2019 • Marc Brittain, Peng Wei
Air traffic control is a real-time safety-critical decision making process in highly dynamic and stochastic environments.
no code implementations • 18 May 2018 • Marc Brittain, Peng Wei
Deep hierarchical reinforcement learning has gained a lot of attention in recent years due to its ability to produce state-of-the-art results in challenging environments where non-hierarchical frameworks fail to learn useful policies.
Hierarchical Reinforcement Learning reinforcement-learning +1