Computationally Modeling Insect Swarms

Swarms of insects and similar species show signs of collective or emergent behaviors. We can analyze these behaviors thoroughly by looking at how the simulated properties are related to different formations of insect swarms. This work focuses on a newly developed computational model. Through incorporating random, but limited, perturbations in velocity direction, we can achieve a combination of stochastic and deterministic outputs. In addition to this new model, we look at the behaviors shown in older models including, but not limited to polarization, diffusion, rotational inertia, distribution of insects, etc. Furthermore, we examine how the use of random number generators can influence computational models, focusing on the spread of randomness in these models from a completely stochastic model, to a completely deterministic model.