Reinforcement Learning has been an up and coming field in Artificial Intelligence, and with the advent of Machine Learning Agents, it has never been a more appropriate time to contribute to the field of reinforcement learning and create an artificial environment where the individual agents can fly around a course, with considerable accuracy, and near perfect flight path, and to incorporate into the multi-agent environment which we created, a human controlled agent, which will compete against the agents which we trained using imitation learning, a Reinforcement Learning Algorithm. The objective of the project is to build agents using Reinforcement Learning to play a First Person Game, in a 3D environment. The Project uses Unity’s ML-Agents Libraries to train competitive AI agents with different reward functions intended to perform particular tasks. We use Imitation Learning and Reinforcement Learning to solve this task and create a smooth and stable gameplay. The airplanes fly freely in space using “Raycast” vision and use reinforcement learning to be trained to fly along the flight path. This Project is my way of paying a tribute to the field of autonomous self-driving tech, which is showing signs of improvement at a tremendous rate, and the science and shows promise with fascinating research, driving the innovations.