Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish.

ABSTRACT: Coordinated motion and collective decision-making in fish schools result from complex interactions by which individuals integrate information about the behavior of their neighbors. However, little is known about how individuals integrate this information to take decisions and control their motion. Here, we combine experiments with computational and robotic approaches to investigate the impact of different strategies for a fish to interact with its neighbors on collective swimming in groups of rummy-nose tetra (Hemigrammus rhodostomus). By means of a data-based agent model describing the interactions between pairs of H. rhodostomus (Calovi et al., 2018), we show that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observe

SUBMITTER: Lei L 

PROVIDER: S-EPMC7098660 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature