Collective Structure

Collective structure research explores how the interactions of individual components within a system—be it robots, cells, or AI models—lead to emergent, coordinated behavior at a larger scale. Current work focuses on developing and applying models like deep neural networks and evolutionary algorithms to understand, predict, and control these emergent patterns, with applications ranging from optimizing robotic swarms and improving medical diagnoses to enhancing the performance of large language models. This field is significant for its potential to improve the design and efficiency of complex systems across diverse domains, offering insights into both natural and artificial collective intelligence.