MetaAgent-X uses end-to-end RL to jointly optimize automatic multi-agent system design and execution, outperforming baselines by up to 21.7% through hierarchical rollouts and stagewise co-evolution.
eight circles of radius 34 are sequentially tangent, and two of the circles are tangent to AB and BC of triangle ABC, respectively
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MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning
MetaAgent-X uses end-to-end RL to jointly optimize automatic multi-agent system design and execution, outperforming baselines by up to 21.7% through hierarchical rollouts and stagewise co-evolution.