Systems and methods for placement of virtual content objects in an extended reality environment based on reinforcement learning

Abstract

In some aspects, the techniques described herein relate to a method including: generating, by a reinforcement learning engine, a plurality of user states within a simulated 3-dimensional environment; generating, by the reinforcement learning engine and for each of the plurality of user states, a plurality of movement actions, wherein each of the plurality of movement actions place a virtual content object in a corresponding position within the simulated 3-dimensional environment; generating, by the reinforcement learning engine and for each corresponding position of the virtual content object, a reward value, wherein the reward value reflects a relative utility of the corresponding position of the virtual content object; and updating, by the reinforcement learning engine, a placement policy based on the reward value for each corresponding position of the virtual content object.