Doubly constrained offline reinforcement learning for learning path recommendation

Yue Yun, Huan Dai, Rui An, Yupei Zhang, Xuequn Shang

Abstract: Highlights•We apply offline reinforcement learning to the task of learning path recommendation.•Our model handls the extrapolation error in RL within educational settings.•The performance of the RL-based system is influenced by the simulated environment