Reinforcement learning in aviation, either unmanned or manned, with an injection of AI

Abstract

We propose a novel theme of aviation with the injection of AI in the form of a reinforcement learning (RL) agent that learns flying skills by observing the pilot’s psychological reaction and flight path in a simulator. The pilot and the RL agent learn flying skills simultaneously, forming a symbiotic relationship. The episodes for training the reinforcement learning agent can be simulated by a pilot flying in a simulator, or unmanned using a game on a computer. In a typical episode, the reinforcement learning agent provides a sequence of actions for the pilot to follow. These instructions produce one of the two types of results, either success or failure. The agent observes the psychological reaction of the pilot as well as the flight environment and receives a positive or negative reward. The trained RL agent represents a novel form of AI that assists the pilot for various phases of flight.