This project explores the application of swarm intelligence in simulating fish behavior evading predators. Utilizing computational algorithms inspired by natural swarms, the simulation aims to mimic the collective movement patterns of fish, optimizing their escape routes. By implementing principles such as repulsion, alignment, and cohesion, the model simulates the coordinated response of a fish swarm to evade predators, contributing to our understanding of collective behaviors in nature.
