Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control
- DOI
- 10.1016/j.mlwa.2026.100919
- Published
- 2026-06
- Container
- Machine Learning with Applications
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.mlwa.2026.100919,
title = {Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control},
author = {Alberto Gil-Maciá and J. Enrique Sierra-García and Matilde Santos},
year = {2026},
journal = {Machine Learning with Applications},
doi = {10.1016/j.mlwa.2026.100919},
url = {https://doi.org/10.1016/j.mlwa.2026.100919}
}RIS
TY - JOUR TI - Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control AU - Alberto Gil-Maciá AU - J. Enrique Sierra-García AU - Matilde Santos PY - 2026 JO - Machine Learning with Applications DO - 10.1016/j.mlwa.2026.100919 UR - https://doi.org/10.1016/j.mlwa.2026.100919 ER -
APA
Gil-Maciá, A., Sierra-García, J. E., & Santos, M. (2026). Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control. Machine Learning with Applications. https://doi.org/10.1016/j.mlwa.2026.100919
Source records
- crossref · retrieved 2026-09-25T14:59:45.054Z