Off-Policy Reinforcement Learning for Tracking in Continuous-Time Systems on Two Time Scales
- DOI
- 10.1109/tnnls.2020.3017461
- Published
- 2021-10
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2020.3017461,
title = {Off-Policy Reinforcement Learning for Tracking in Continuous-Time Systems on Two Time Scales},
author = {Wenqian Xue and Jialu Fan and Victor G. Lopez and Yi Jiang and Tianyou Chai and Frank L. Lewis},
year = {2021},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2020.3017461},
url = {https://doi.org/10.1109/tnnls.2020.3017461}
}RIS
TY - JOUR TI - Off-Policy Reinforcement Learning for Tracking in Continuous-Time Systems on Two Time Scales AU - Wenqian Xue AU - Jialu Fan AU - Victor G. Lopez AU - Yi Jiang AU - Tianyou Chai AU - Frank L. Lewis PY - 2021 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2020.3017461 UR - https://doi.org/10.1109/tnnls.2020.3017461 ER -
APA
Xue, W., Fan, J., Lopez, V. G., Jiang, Y., Chai, T., & Lewis, F. L. (2021). Off-Policy Reinforcement Learning for Tracking in Continuous-Time Systems on Two Time Scales. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2020.3017461
Source records
- crossref · retrieved 2026-11-10T09:48:41.793Z