Quantum reinforcement learning in continuous action space
Quantum reinforcement learning (QRL) is a promising paradigm for near-term quantum devices. While existing QRL methods have shown success in discrete action spaces, extending these techniques to continuous domains is challenging due to the curse of dimensionality introduced by discretization. To ove...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2025-03-01
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| Series: | Quantum |
| Online Access: | https://quantum-journal.org/papers/q-2025-03-12-1660/pdf/ |
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