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This paper investigates information propagation and threat evasion in cognitive flocks using numerical simulations of an augmented inertial spin model with an explicit predator. The augmented inertial spin model demonstrates nearly linear information propagation in the under-damped regime, even with realistic flocking behaviors, and identifies an optimal balance for turning distance based on response strength, flock speed, and damping. The research reveals that fast information propagation is crucial for maintaining flock cohesion under pursuit and that flock geometry significantly influences collective escape dynamics when facing multiple predators.
Cognitive flocks can maintain cohesion and escape predators effectively by synchronizing responses through fast, nearly linear information propagation, even amidst complex local interactions.
Information sharing, threat perception, and collective evasion highlight the advantages of swarm intelligence. Here, we study the behavior of flocks of cognitive agents, based on numerical simulations of the augmented inertial spin model, with an explicit predator. Each agent on the predator-facing side of the flock perceives the threat, triggering collective turns through local interactions. We show that the augmented inertial spin model sustains nearly linear information propagation in the under-damped regime, even with realistic flocking interactions such as local collision avoidance and swarm cohesion in addition to alignment. The turning distance of the flock to a stationary predator scales with the ratio $\Delta_p/(v_0\sqrt{\eta})$, identifying an optimal balance between response strength $\Delta_p$, flock speed $v_0$, and damping $\eta$ of information propagation. Fragmentation arises when different parts of the flock turn in different directions, however, fast information propagation can synchronize these responses and maintain flock cohesion while under pursuit. For two predators, a combination of stability analysis and simulations reveals a stark contrast between flock and single-particle reactions, with scattering angle shaped by flock geometry, predator position, and the heterogeneous responses of the detecting front. Together, these results show how information propagation, flock geometry, and dynamics together shapes collective escape, providing general principles relevant to both biological flocks and robotic swarms.