Collective behaviour across animal species

被引:46
|
作者
DeLellis, Pietro [1 ,2 ]
Polverino, Giovanni [2 ]
Ustuner, Gozde [2 ]
Abaid, Nicole [3 ]
Macri, Simone [4 ]
Bollt, Erik M. [5 ]
Porfiri, Maurizio [2 ]
机构
[1] Univ Naples Federico II, Dept Elect Engn & Informat Technol, I-80125 Naples, Italy
[2] NYU, Polytech Sch Engn, Dept Mech & Aerosp Engn, Brooklyn, NY 11201 USA
[3] Virginia Polytech Inst & State Univ, Dept Engn Sci & Mech, Blacksburg, VA 24061 USA
[4] Ist Super Sanita, Sect Behav Neurosci, Dept Cell Biol & Neurosci, I-00161 Rome, Italy
[5] Clarkson Univ, Dept Math, Potsdam, NY 13699 USA
来源
SCIENTIFIC REPORTS | 2014年 / 4卷
基金
美国国家科学基金会;
关键词
ZEBRAFISH;
D O I
10.1038/srep03723
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:6
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