Learning Families of Fixed-Wing Aircraft Control Policies with Hypernetwork-Conditioned Reinforcement Learning

This paper investigates whether it is more effective to condition reinforcement learning policies across changing dynamics using standard input augmentation or hypernetwork-based parameter modulation. We use a small fixed-wing uncrewed aircraft under actuator failures as a demanding test case, as th