Distributional Reinforcement Learning for Flight Control: A risk-sensitive approach to aircraft attitude control using Distributional RL

With the recent increase in the complexity of aerospace systems and autonomous operations, there is a need for an increased level of adaptability and model-free controller synthesis. Such operations require the controller to maintain safety and performance without human intervention in non-static environments with partial observability and...