How Reinforcement Learning Transforms E‑Commerce Search and Recommendation at Scale
This article explores how Alibaba's Taobao leverages reinforcement learning, Markov decision processes, and reward shaping to improve large‑scale product search ranking and recommendation, detailing problem modeling, algorithm designs such as Tabular Q‑learning and DDPG, experimental results, and advanced recommendation models like GBDT‑FTRL and Wide‑Deep.
