Mobile Notification

Mobile notification optimization aims to improve user engagement and satisfaction by intelligently deciding which notifications to send, when, and how. Current research heavily focuses on reinforcement learning (RL) approaches, including model-based RL and offline RL methods like Double Deep Q-networks, to optimize for long-term user value and address the sequential nature of notification interactions. These methods are contrasted with and often outperform simpler heuristic-based systems and traditional ranking algorithms. The resulting improvements in notification delivery lead to increased user engagement with reduced notification fatigue, impacting both the design of recommender systems and the overall user experience on mobile platforms.