Targeted interventions via long term reward attribution in complex software ecosystems

Abstract

Aspects of the present disclosure provide techniques for dynamic reward-driven intervention in a software application. Embodiments include determining rewards associated with user actions in the software application using a reward machine learning model trained based on prior instances of the user actions associated with values for a target attribute, each of the prior instances of the user actions being performed within a particular time interval following a prior intervention provided via the software application. Embodiments include providing interventions to a user via the software application. Embodiments include detecting that the user has performed one or more respective user actions of the user actions after the providing of each intervention of the interventions. Embodiments include training an intervention machine learning model based on the detecting and the rewards. Embodiments include providing a targeted intervention to the user via the software application based on the training of the intervention machine learning model.