Configuring execution of a service in a distributed services system

Abstract

Disclosed herein are methods and systems for improved service system configuration during distributed services execution by a distributed services system. In one example, different sets of machine learning models respectively generate signals indicative of predicted risk and expected values associated with execution of a service by the distributed services system. Next, expected values associated with actions, where each action corresponds to a configuration of the service, are determined so that an action that maximizes the expected value associated with the execution of the service based on the predicted risk can be selected. The action is then executed configuring the execution of the service for a user in the distributed services system.