MAF-RL

MAF-RL is a RecBole-based research framework for Multi-Modal Actor–Critic Reinforcement Learning in sequential recommendation. It integrates multimodal feature fusion, PPO optimization, and scalable evaluation on real-world datasets such as MovieLens, Amazon, and Yelp.