title: Collective behaviour across animal species.
abstract: We posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment.
authors.affiliation: 1] Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples 80125, Italy [2] Department of Mechanical and Aerospace Engineering, Polytechnic School of Engineering, New York University, Brooklyn, New York 11201, USA.
authors.forename: Pietro
authors.initials: P
authors.lastname: DeLellis
authors.affiliation: Department of Mechanical and Aerospace Engineering, Polytechnic School of Engineering, New York University, Brooklyn, New York 11201, USA.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Polverino
authors.affiliation: Department of Mechanical and Aerospace Engineering, Polytechnic School of Engineering, New York University, Brooklyn, New York 11201, USA.
authors.forename: Gozde
authors.initials: G
authors.lastname: Ustuner
authors.affiliation: Department of Engineering Science and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.
authors.forename: Nicole
authors.initials: N
authors.lastname: Abaid
authors.affiliation: Section of Behavioural Neuroscience, Department of Cell Biology and Neuroscience, Istituto Superiore di Sanità, Roma 00161, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Macrì
authors.affiliation: Department of Mathematics, Clarkson University, Potsdam, New York 13699, USA.
authors.forename: Erik M
authors.initials: EM
authors.lastname: Bollt
authors.affiliation: Department of Mechanical and Aerospace Engineering, Polytechnic School of Engineering, New York University, Brooklyn, New York 11201, USA.
authors.forename: Maurizio
authors.initials: M
authors.lastname: Porfiri
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D001522:Behavior, Animal; D013045:Species Specificity