Deep Reinforcement Learning in Simulated Aerial Battlespace

Long has reinforcement learning been used to teach AI to play games and learn in a simulated environment. The goal of this project is to use the same idea in real world aerial combat. By Using deep learning agents to engage in combat and learn the best tactics to achieve air superiority, shooting down enemy planes, and attacking enemy ground bases in a simulated environment. With the results being able to teach fighter pilots and autonomous drones the best possible tactics.