ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation

要約

Proactive Recommender Systems (PRSs) aim to guide user preference shift toward target items by generating paths of intermediate recommendations. Reinforcement learning (RL) provides a principled framework for optimizing such sequential decision tasks, as path rewards can naturally capture both short…