Мультиагентне навчання з підкріпленням для оптимізації квантових схем
The article presents an approach to quantum circuit optimization based on Multi-Agent Reinforcement Learning (MARL), which integrates the MAPPO algorithm with Graph Neural Networks (GNNs). The relevance of the research stems from the need to reduce gate counts and circuit depth in quantum compilatio...
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| Date: | 2025 |
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| Main Authors: | , |
| Format: | Article |
| Language: | Ukrainian |
| Published: |
V.M. Glushkov Institute of Cybernetics of NAS of Ukraine
2025
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| Subjects: | |
| Online Access: | https://jais.net.ua/index.php/files/article/view/531 |
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| Journal Title: | Problems of Control and Informatics |