Floris den Hengst
Cited by
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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
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
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
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
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
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
Learning to Behave: Reinforcement Learning in Human Contexts
F den Hengst
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
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
Low-Variance Policy Gradient Estimation with World Models
M Nauman, FD Hengst
arXiv preprint arXiv:2010.15622, 2020
Detecting Interesting Outliers
F den Hengst, M Hoogendoorn, D Jonker
VU Research Portal
M Nauman, FD Hengst
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