Reinforcement Learning as a tool to make people move to a specific location in Immersive Virtual Reality

This paper describes the use of Reinforcement Learning in Immersive Virtual Reality to make a person move to a specific location in a virtual environment. Reinforcement Learning is a sub-area of Machine Learning in which an active entity called an agent interacts with its environment and learns how to act in order to achieve a predetermined goal. The Reinforcement Learning had no prior model of behaviour and the participants no prior knowledge that their task was to move to and stay in a specific place. The participants were placed in a virtual environment where they had to avoid collisions with virtual projectiles. Following each projectile the agent analysed the movement made by the participant to determine paths of future projectiles in order to increase the chance of driving participants to the goal position and make them stay there as long as possible. The experiment was carried out with 30 participants, 10 were guided towards the leftmost part of the environment, 10 to the rightmost area, and 10 were used as control group where the projectiles were shot randomly throughout the game. Our results show that people tended to stay close to the target area in both the Left and Right conditions, but not in the Random condition.