Reinforcement Learning Based Control for Unmanned Aerial Vehicles

Estates, especially those of public securityrelated companies and institutes, have to protect their privacy from adversary unmanned aerial vehicles(UAVs). In this paper, we propose a reinforcement learning-based control framework to prevent unauthorized UAVs from entering a target area in a dynamic game without being aware of the UAV attack model. This UAV control scheme enables a target estate to choose the optimal control policy, such as jamming the global positioning system signals, hacking,