Intelligently modifying digital calendars utilizing a graph neural network and reinforcement learning

Abstract

This disclosure describes methods, non-transitory computer readable storage media, and systems that intelligently generate and modify schedules of task sequences utilizing a graph neural network and/or reinforcement learning model. For example, the disclosed system utilizes a graph neural network to generate performance efficiency scores indicating predicted performances of the sets of tasks. Additionally, the disclosed systems utilizes the performance efficiency scores to rank sets of tasks and then determine a schedule including an ordered sequence of tasks. Furthermore, disclosed system generates modified schedules in response to detecting a modification to the schedule. For example, the disclosed system utilizes a reinforcement learning model to provide recommendations of new tasks or task sequences deviating from the schedule in the event of an interruption. The disclosed system also utilizes the reinforcement learning model to learn from user choices to inform future scheduling of tasks.