q-Learning in Continuous Time
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Cited by:
- Hidekazu Yoshioka, 2024. "Generalized Logit Dynamics Based on Rational Logit Functions," Dynamic Games and Applications, Springer, vol. 14(5), pages 1333-1358, November.
- Min Dai & Yuchao Dong & Yanwei Jia & Xun Yu Zhou, 2023. "Learning Merton's Strategies in an Incomplete Market: Recursive Entropy Regularization and Biased Gaussian Exploration," Papers 2312.11797, arXiv.org.
- Yanwei Jia, 2024. "Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty," Papers 2404.12598, arXiv.org.
- Xiaoli Wei & Xiang Yu & Fengyi Yuan, 2024. "Unified continuous-time q-learning for mean-field game and mean-field control problems," Papers 2407.04521, arXiv.org.
- Xia Han & Ruodu Wang & Xun Yu Zhou, 2022. "Choquet regularization for reinforcement learning," Papers 2208.08497, arXiv.org.
- Xiangyu Cui & Xun Li & Yun Shi & Si Zhao, 2023. "Discrete-Time Mean-Variance Strategy Based on Reinforcement Learning," Papers 2312.15385, arXiv.org.
- Xuefeng Gao & Lingfei Li & Xun Yu Zhou, 2024. "Reinforcement Learning for Jump-Diffusions, with Financial Applications," Papers 2405.16449, arXiv.org, revised Aug 2024.
- Min Dai & Yu Sun & Zuo Quan Xu & Xun Yu Zhou, 2024. "Learning to Optimally Stop Diffusion Processes, with Financial Applications," Papers 2408.09242, arXiv.org, revised Sep 2024.
- Lijun Bo & Yijie Huang & Xiang Yu, 2023. "On optimal tracking portfolio in incomplete markets: The reinforcement learning approach," Papers 2311.14318, arXiv.org, revised Oct 2024.
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This paper has been announced in the following NEP Reports:- NEP-BIG-2022-08-15 (Big Data)
- NEP-CMP-2022-08-15 (Computational Economics)
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