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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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IOP Publishing
2024-01-01
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| Серии: | Machine Learning: Science and Technology |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1088/2632-2153/ad6830 |
| Метки: |
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