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Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design

Research article (Quantum Reports, 2022) · cited 12× · AI/ML
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Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design

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Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design is a scholarly article[1].

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  • Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design. Retrieved May 24, 2026, from https://4ort.xyz/entity/model-free-deep-recurrent-q-network-reinforcement-learning-for-quantum-circuit-architectures-design
MLA “Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/model-free-deep-recurrent-q-network-reinforcement-learning-for-quantum-circuit-architectures-design.
BibTeX @misc{4ortxyz_model-free-deep-recurrent-q-network-reinforcement-learning-for-quantum-circuit-architectures-design_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design}}, year = {2026}, url = {https://4ort.xyz/entity/model-free-deep-recurrent-q-network-reinforcement-learning-for-quantum-circuit-architectures-design}, note = {Accessed: 2026-05-24}}
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