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Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups

Overview of attention for article published in PLoS ONE, August 2011
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1 tweeter

Citations

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Title
Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups
Published in
PLoS ONE, August 2011
DOI 10.1371/journal.pone.0022827
Pubmed ID
Authors

Richard P. Mann

Abstract

The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of "universal" classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Germany 2 2%
Switzerland 1 1%
Spain 1 1%
Indonesia 1 1%
Brazil 1 1%
Japan 1 1%
India 1 1%
Belgium 1 1%
Other 1 1%
Unknown 69 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 21%
Student > Master 13 16%
Professor 12 15%
Student > Ph. D. Student 12 15%
Professor > Associate Professor 5 6%
Other 22 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 44%
Physics and Astronomy 8 10%
Computer Science 6 7%
Mathematics 5 6%
Environmental Science 5 6%
Other 21 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 August 2011.
All research outputs
#9,067,092
of 11,324,871 outputs
Outputs from PLoS ONE
#93,983
of 125,959 outputs
Outputs of similar age
#68,060
of 88,033 outputs
Outputs of similar age from PLoS ONE
#1,387
of 1,790 outputs
Altmetric has tracked 11,324,871 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 125,959 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 88,033 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,790 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.