Collective behavior as a research area investigates how large ensembles of interacting agents—such as cells, animals, humans, or artificial units—generate emergent spatiotemporal patterns and coordinated dynamics that cannot be trivially inferred from individual-level rules. It integrates concepts and methods from statistical physics, nonlinear dynamics, complex systems theory, network science, and computational modeling to characterize phenomena such as synchronization, swarming, flocking, consensus formation, and phase transitions in social or biological systems. Research focuses on identifying local interaction rules, quantifying macroscopic order parameters, understanding robustness and criticality, and developing predictive, often multi-scale, models of group-level organization and decision-making.
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