Decomposing sequence design into cooperative multi-agent sub-problems with centralized guidance improves both the quality and speed of RNA structure prediction compared to single-agent approaches.
CocoRNA uses multiple AI agents working together to design RNA sequences that fold into specific shapes. By breaking the complex design problem into smaller parts and having agents collaborate with guidance from a central critic, the system learns to create better RNA designs faster than existing methods.