Reinforcement learning for personalization: A systematic literature review F Den Hengst, EM Grua, A el Hassouni, M Hoogendoorn Data Science 3 (2), 107-147, 2020 | 33 | 2020 |
Reinforcement learning for personalized dialogue management F Den Hengst, M Hoogendoorn, F Van Harmelen, J Bosman IEEE/WIC/ACM International Conference on Web Intelligence, 59-67, 2019 | 16 | 2019 |
Planning for potential: efficient safe reinforcement learning F Den Hengst, V François-Lavet, M Hoogendoorn, F van Harmelen Machine Learning 111 (6), 2255-2274, 2022 | 11 | 2022 |
Reinforcement learning with option machines F den Hengst, V François-Lavet, M Hoogendoorn, F van Harmelen Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 5 | 2022 |
Log parsing evaluation in the era of modern software systems S Petrescu, F Den Hengst, A Uta, JS Rellermeyer 2023 IEEE 34th International Symposium on Software Reliability Engineering …, 2023 | 1 | 2023 |
Collecting high-quality dialogue user satisfaction ratings with third-party annotators M van Zeelt, F den Hengst, SH Hashemi Proceedings of the 2020 Conference on Human Information Interaction and …, 2020 | 1 | 2020 |
Learning to Behave: Reinforcement Learning in Human Contexts F den Hengst | | 2023 |
Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment M Otten, AR Jagesar, TA Dam, LA Biesheuvel, F den Hengst, ... Critical Care Medicine, 10.1097, 2023 | | 2023 |
Strategic Workforce Planning with Deep Reinforcement Learning Y Smit, F den Hengst, S Bhulai, E Mehdad International Conference on Machine Learning, Optimization, and Data Science …, 2022 | | 2022 |
Low-Variance Policy Gradient Estimation with World Models M Nauman, FD Hengst arXiv preprint arXiv:2010.15622, 2020 | | 2020 |
Detecting Interesting Outliers F den Hengst, M Hoogendoorn, D Jonker | | 2016 |
VU Research Portal M Nauman, FD Hengst | | |