Trainability issues in quantum policy gradients
This research explores the trainability of Parameterized Quantum Circuit-based policies in Reinforcement Learning, an area that has recently seen a surge in empirical exploration. While some studies suggest improved sample complexity using quantum gradient estimation, the efficient trainability of t...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
IOP Publishing
2024-01-01
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| Serie: | Machine Learning: Science and Technology |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1088/2632-2153/ad6830 |
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