Model Imitation for Model-Based Reinforcement Learning

Model-based reinforcement learning (MBRL) aims to learn a dynamic model to reduce the number of interactions with real-world environments.

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Yueh-Hua Wu, Ting-Han Fan, Peter J. Ramadge, Hao Su (2024). Dataset: Model Imitation for Model-Based Reinforcement Learning. https://doi.org/10.57702/exed8x23

DOI retrieved: December 2, 2024

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Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.1909.11821
Author Yueh-Hua Wu
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Ting-Han Fan
Peter J. Ramadge
Hao Su