Adaptivni računalniški model skupinskega vedenja plena ob napadu plenilca.

Computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. Based on empirical studies and existing models of collective behaviour there are four distinct types of behaviour: swarming, milling, dynamic parallel movement, and highly parallel movement. Swarming is most often associated with insects. Milling, where individuals perpetually rotate around an empty core, can at special occasions be exhibited by fish schools. Dynamic and highly parallel movement is most often associated with bird flocks and fish schools. In the existing models, these types of behaviour are achieved by tuning certain parameters of the model. In this paper we present an adaptive individual-based model of a prey group facing predator attacks; the prey group adapts its behaviour by changing specific parameters based on the predators' distance. Using a genetic algorithm we investigate a) which type of behaviour is the optimal defence against various predation tactics, and b) if the prey group will resort to transitions between various types of behaviour as a form of advanced defence tactic. [ABSTRACT FROM AUTHOR]