Researchers from Seoul National University and Kyung Hee University have developed a groundbreaking AI framework that learns the local rules behind flocking and collective motion behaviors. By combining principles from physics with advanced artificial intelligence, the team can now control and predict how groups—like birds or fish—move together in patterns such as rings, clumps, mills, or flocks.
Revolutionizing Collective Behavior Understanding
The new physics-informed AI model learns from real-world observations. It identifies the local interaction rules that cause large-scale coordinated movements, a challenge that has long puzzled scientists. This approach lets researchers not only analyze but also manipulate collective behaviors in both natural and artificial systems. Potential applications include robotics, environmental monitoring, and crowd management.
Future Possibilities
By teaching AI to understand the underlying dynamics of group movement, scientists open up new possibilities in swarm robotics and automated systems. The ability to control collective motion could lead to improvements in transportation, surveillance, and even entertainment industries.
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