Video Recommendation with Multi-gate Mixture of Experts Soft Actor Critic

Abstract

In this paper, we propose a reinforcement learning based large scale multi-objective ranking system for optimizing short-video recommendation on an industrial video sharing platform. Multiple competing ranking objective and implicit selection bias in user feedback are the main challenges in real-world platform. In order to address those challenges, we integrate multi-gate mixture of experts and soft actor critic into the ranking system. We demonstrated that our proposed framework can greatly reduce the loss function compared with systems only based on single strategies.