Multi-Agent-Based Dynamic Model of Fish Collective Behavior

In the natural world, numerous fish species exhibit collective behavior to gain advantages, such as improved foraging, predator avoidance, and swimming efficiency. However, the mechanisms underlying the formation of these collective behaviors remain unclear. To investigate this phenomenon and elucidate its underlying principles, we have developed a dynamic model incorporating empirical social rules and fluid hydrodynamic effects, including the intricate wake patterns that trail swimming fish. By leveraging this flow-physics-informed approach, we can simulate the collective swimming behavior of fish in diverse scenarios with remarkable realism and comprehensiveness.

Cite as: Ji Zhou, Jung-Hee Seo, Rajat Mittal; Effect of hydrodynamic wakes in dynamical models of large-scale fish schools. Physics of Fluids 1 January 2025; 37 (1): 011912. https://doi.org/10.1063/5.0250013

Animations of fish schooling using the dynamic multi-agent-based model.