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Lifelong Hyper-Policy Optimization with Multiple Importance Sampling

The authors propose a lifelong RL approach that learns a hyper-policy, whose input is time, that outputs the parameters of the policy to be queried at that time.

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Cite this as

Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli (2024). Dataset: Lifelong Hyper-Policy Optimization with Multiple Importance Sampling. https://doi.org/10.57702/ron28kil

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2112.06625
Author	Pierre Liotet
More Authors	Francesco Vidaich Alberto Maria Metelli Marcello Restelli