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Wang, Jiao Zhang, Lemin He, Zhiqiang Zhu, Can and Zhao, Zihui 2022. Erlang planning network: An iterative model-based reinforcement learning with multi-perspective. Pattern Recognition, Vol. 128, Issue. , p. 108668.
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Ye, Rongjun Wang, Hao and Li, Huan 2022. Safe Deep Reinforcement Learning Based on Sample Value Evaluation. p. 161.
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Huang, Zhigang Liu, Quan and Zhu, Fei 2023. Hierarchical reinforcement learning with adaptive scheduling for robot control. Engineering Applications of Artificial Intelligence, Vol. 126, Issue. , p. 107130.
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Huang, Zhigang Liu, Quan Zhu, Fei Zhang, Lihua and Wu, Lan 2024. Hierarchical reinforcement learning with unlimited option scheduling for sparse rewards in continuous spaces. Expert Systems with Applications, Vol. 237, Issue. , p. 121467.
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Zhou, Yuhao Wang, Xiaoming Wang, Xinzhi Xie, Shaorong Zhang, ZhenYu Jabbar , M. A. and Lorenz, Pascal 2024. Reducing redundancy of skills in hierarchical reinforcement learning with offline data. p. 79.
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Huang, Zhigang 2024. Discovering and Exploiting Skills in Hierarchical Reinforcement Learning. IEEE Access, Vol. 12, Issue. , p. 163042.
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Safe option-critic: learning safety in the option-critic architecture
  • Volume 36
  • Arushi Jain (a1), Khimya Khetarpal (a1) and Doina Precup (a1)
  • DOI: https://doi.org/10.1017/S0269888921000035
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Safe option-critic: learning safety in the option-critic architecture
  • Volume 36
  • Arushi Jain (a1), Khimya Khetarpal (a1) and Doina Precup (a1)
  • DOI: https://doi.org/10.1017/S0269888921000035
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Safe option-critic: learning safety in the option-critic architecture
  • Volume 36
  • Arushi Jain (a1), Khimya Khetarpal (a1) and Doina Precup (a1)
  • DOI: https://doi.org/10.1017/S0269888921000035
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