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arXiv Machine Learning By Tianmeng Hu, Biao Luo, Ke Li

CocoRNA: Collective RNA Design with Cooperative Multi-agent Reinforcement Learning

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CocoRNA is a cooperative multi-agent reinforcement learning framework that tackles RNA inverse design by breaking the problem into smaller sub‑problems solved collaboratively by multiple agents. A centralized critic provides global structural guidance during training, allowing the agents to jointly optimize their design strategies. Experiments on the Rfam dataset show that CocoRNA outperforms state‑of‑the‑art methods in both success rate and design speed, and additional tests on other biological sequence design tasks demonstrate its broad effectiveness.

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