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Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning.

, and . EDM, page 507-512. International Educational Data Mining Society (IEDMS), (2016)

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Hierarchical Reinforcement Learning for Pedagogical Policy Induction., , , , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 544-556. Springer, (2019)A Unified Batch Hierarchical Reinforcement Learning Framework for Pedagogical Policy Induction with Deep Bisimulation Metrics., , , and . AIED (Posters/Late Breaking Results/...), volume 1831 of Communications in Computer and Information Science, page 599-605. Springer, (2023)Exploring the Effect of Autoencoder Based Feature Learning for a Deep Reinforcement Learning Policy for Providing Proactive Help., , , and . AIED (Posters/Late Breaking Results/...), volume 1831 of Communications in Computer and Information Science, page 278-283. Springer, (2023)Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions., , , , and . EDM (Workshops), volume 2592 of CEUR Workshop Proceedings, page 69-78. CEUR-WS.org, (2019)Using the Hint Factory to Compare Model-Based Tutoring Systems., , , and . EDM (Workshops), volume 1446 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)What Time is It? Student Modeling Needs to Know., , , , and . EDM, International Educational Data Mining Society, (2020)Latent Space Encoding for Interpretable Fuzzy Logic Rules in Continuous and Noisy High-Dimensional Spaces., and . FUZZ, page 1-6. IEEE, (2023)Exploring the Impact of Worked Examples in a Novice Programming Environment., , , , , and . SIGCSE, page 98-104. ACM, (2019)Reinforcement Learning-based Feature Seleciton For Developing Pedagogically Effective Tutorial Dialogue Tactics., , , and . EDM, page 258-265. www.educationaldatamining.org, (2008)Evolving Augmented Graph Grammars for Argument Analysis., , and . GECCO (Companion), page 65-66. ACM, (2016)