title: A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments.
abstract: Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences.
authors.affiliation: Université Paris Diderot , Sorbonne Paris Cité, LIED, UMR 8236, 75013 Paris, France.
authors.forename: Bertrand
authors.initials: B
authors.lastname: Collignon
authors.affiliation: Université Paris Diderot , Sorbonne Paris Cité, LIED, UMR 8236, 75013 Paris, France.
authors.forename: Axel
authors.initials: A
authors.lastname: Séguret
authors.affiliation: Université Paris Diderot , Sorbonne Paris Cité, LIED, UMR 8236, 75013 Paris, France.
authors.forename: José
authors.initials: J
authors.lastname: Halloy
keywords: agent-based model; collective motion; solid angle; visual perception; zebrafish