Multi-dimensional reinforcement learning in an ai platform

Abstract

Examples in the present disclosure relate to multi-dimensional reinforcement learning in a digital platform. The digital platform maintains and updates user data associated with tracked users. One or more machine learning models process the user data to generate recommendation data that includes automatically generated exploratory program elements for known activity programs of respective users of the digital platform. The exploratory program elements are validated by supervising users before implementation. The digital platform continuously updates the one or more machine learning models using dual reinforcement signals: one based on supervising user-validated recommendations and another based on activity program results. Further recommendation data is generated after updating the one or more machine learning models.