arXiv Machine Learning July 13, 2026 By Edwin De Nicolo, Rahul Marchand, Cornelius Carlsson, Pranav Vaidhyanathan, Natalia Ares

Action-Factored Multi-Agent Reinforcement Learning for Scalable Quantum Device Tuning

Read the original on arXiv Machine Learning →

arXiv:2607. 09422v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning is well suited to problems with large parameter spaces and exploitable local structure, such as the tuning of electrostatically-defined quantum-dot arrays.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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