Privileged Knowledge State Distillation for Reinforcement Learning-based Educational Path Recommendation

Author:

Li Qingyao1ORCID,Xia Wei2ORCID,Yin Li'ang1ORCID,Jin Jiarui1ORCID,Yu Yong1ORCID

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Huawei Noah's Ark Lab, Shenzhen, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Reference42 articles.

1. 2020. MindSpore. https://www.mindspore.cn/

2. Mohammadamin Barekatain, Ryo Yonetani, and Masashi Hamaya. 2019. Multipolar: Multi-source policy aggregation for transfer reinforcement learning between diverse environmental dynamics. arXiv preprint arXiv:1909.13111 (2019).

3. Adaptive learning path recommendation based on graph theory and an improved immune algorithm;Bian Cun-Ling;KSII Transactions on Internet and Information Systems (TIIS),2019

4. Haw-Shiuan Chang Hwai-Jung Hsu and Kuan-Ta Chen. 2015. Modeling Exercise Relationships in E-Learning: A Unified Approach.. In EDM. 532--535.

5. Ontology-based concept map for planning a personalised learning path

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