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Quantification of collective behaviour via causality analysis
by
Rychtáriková, Renata
, Štys, Dalibor
, Lonhus, Kirill
in
Aquariums
/ Causality
/ Complexity
/ Computational Intelligence
/ Data explanatory analysis
/ Data Structures and Information Theory
/ Engineering
/ Ethology
/ Experiments
/ Fish
/ Hypotheses
/ Intelligent systems
/ Network analysis
/ Network graphs
/ Original Article
/ Quantitative behaviour
/ Wolves
2023
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Quantification of collective behaviour via causality analysis
by
Rychtáriková, Renata
, Štys, Dalibor
, Lonhus, Kirill
in
Aquariums
/ Causality
/ Complexity
/ Computational Intelligence
/ Data explanatory analysis
/ Data Structures and Information Theory
/ Engineering
/ Ethology
/ Experiments
/ Fish
/ Hypotheses
/ Intelligent systems
/ Network analysis
/ Network graphs
/ Original Article
/ Quantitative behaviour
/ Wolves
2023
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Quantification of collective behaviour via causality analysis
by
Rychtáriková, Renata
, Štys, Dalibor
, Lonhus, Kirill
in
Aquariums
/ Causality
/ Complexity
/ Computational Intelligence
/ Data explanatory analysis
/ Data Structures and Information Theory
/ Engineering
/ Ethology
/ Experiments
/ Fish
/ Hypotheses
/ Intelligent systems
/ Network analysis
/ Network graphs
/ Original Article
/ Quantitative behaviour
/ Wolves
2023
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Quantification of collective behaviour via causality analysis
Journal Article
Quantification of collective behaviour via causality analysis
2023
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Overview
Terms such as
leader
,
mediator
, and
follower
sound equal in the description of a pack of wolves, a street protest crowd, or a business team and have very similar meanings. This indicates the presence of some general law or structure that governs collective behaviour. To reveal this, we selected the most common parameter for most levels of the organisation—motion. A causality analysis of distance correlations was performed to obtain follow-up networks that show who follows whom and how strongly. These networks characterise an observed system in general and work as an automation bridge between the biological experiment and the broad field of network analysis. The proposed method was tested on 3D image data from a controlled experiment on a 6-member school of aquarium fish of Tiger Barb. The network patterns can be easily ethologically interpreted and agreed with expected behaviour.
Publisher
Springer International Publishing,Springer Nature B.V,Springer
Subject
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