Unmanned swarm systems are revolutionizing fields from disaster relief to military reconnaissance, yet two obstacles have long hindered their reliability: precise trajectory prediction and transparent understanding of swarm interactions. Researchers at Northwestern Polytechnical University have now proposed a solution with their Swarm Relational Inference (SRI) model, published in the Chinese Journal of Aeronautics.

The SRI framework integrates swarm dynamics with dynamic graph neural networks to create physically interpretable and data-driven models of swarm motion. This approach avoids the pitfalls of unrealistic predictions or opaque "black box" methods, allowing explicit mapping between classical swarm rules like separation and cohesion and the features learned by the network.

At its

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