In nature we can find various shapes of collective behavior such as flocks of birds, schools of fish, swarms of insects and herds of grazing animals. In research of evolution of group behavior accurate modelling of animal behavior and their natural habitat is to complex therefor we help ourselves with simplified models of animals and their habitats. We try to find different rules, properties and knowledge as to why and how collective behavior came to evolve. In these models, researchers mostly investigate various properties of collective behavior like: transfer of information between entities, benefits of grouping (defense against predators and foraging), group behavior types and group decision-making processes based on different situations (different habitats or ratio of different predators).
In our master thesis we expanded the model and analysis of Demšar and co-workers [doi: 10.1371/journal.pone.0168876, 10.1038/srep39428]. We were mostly focused on how different shapes of habitats, ratio of different predators, spawn locations of predators and type of simulation loop influence development of four different types of group behavior regimes: polarized, milling, swarming and transition. We implemented two additional habitats, infinite lattice and polygon to add to the set of already implemented circle and square. We also analyzed how spawning predators within living areas differentiates from spawning predators outside of a living area. At the end we also compared the effects of different implementations of asynchronous simulation loop in comparison to synchronized simulation loop. We were especially interested if the latest findings in this field, that asynchronous simulation loop increases the chance for strongly polarized regime to evolve is also true for our model.