Speaker
Description
In a striking example of collective behavior, swarms of locusts march in an apparently coordinated direction. Various swarm morphologies emerge in these groups that aid in feeding or migration, depending on the environment through which the swarm moves. However, unlike eusocial insects (such bees or ants) locusts have no social structure (or queen) to facilitate this directed motion. Instead, agent-based models with identical individuals are a natural lense with which to study the collective motion of locusts. In this talk, we will introduce a framework for evaluating the appropriateness of several models for individual interaction. The work is made possible by recent advances in the availability and magnitude of trajectory data on individual locusts within a swarm. We formulate a Bayesian particle filter to estimate parameters of a given model for individual interaction based on these data. We next conduct a simulation study using the given model with parameters from the posterior distribution. Finally, we compare quantities aggregated from the simulated data and the empirical data to determine if the model recreates similar collective motion.
