Reinforcement learning for controlling software update timing

Abstract

Described herein is a software update distribution service that leverages reinforcement learning—a specific type machine learning algorithm—to discover or learn optimal times (e.g., a schedule) to download software updates and to install software updates for software applications installed on a group of client computing devices of a specific enterprise, in order to achieve one of several predefined goals or objectives selected for the specific enterprise, or for the specific group of client computing devices. Using reinforcement learning, a software-based agent learns to perform activities relating to software updates at specific times that minimize a penalty, wherein the penalty is derived based on a weighted combination of metrics, some of which relate to the impact of software update timing on network traffic and power consumption.