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Solving the shepherding problem: heuristics for herding autonomous, interacting agents

Overview of attention for article published in Journal of The Royal Society Interface, November 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 2,641)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
16 news outlets
blogs
3 blogs
twitter
83 tweeters
facebook
6 Facebook pages
googleplus
4 Google+ users
reddit
1 Redditor
video
1 video uploader

Citations

dimensions_citation
76 Dimensions

Readers on

mendeley
125 Mendeley
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Title
Solving the shepherding problem: heuristics for herding autonomous, interacting agents
Published in
Journal of The Royal Society Interface, November 2014
DOI 10.1098/rsif.2014.0719
Pubmed ID
Authors

Daniel Strömbom, Richard P. Mann, Alan M. Wilson, Stephen Hailes, A. Jennifer Morton, David J. T. Sumpter, Andrew J. King

Abstract

Herding of sheep by dogs is a powerful example of one individual causing many unwilling individuals to move in the same direction. Similar phenomena are central to crowd control, cleaning the environment and other engineering problems. Despite single dogs solving this 'shepherding problem' every day, it remains unknown which algorithm they employ or whether a general algorithm exists for shepherding. Here, we demonstrate such an algorithm, based on adaptive switching between collecting the agents when they are too dispersed and driving them once they are aggregated. Our algorithm reproduces key features of empirical data collected from sheep-dog interactions and suggests new ways in which robots can be designed to influence movements of living and artificial agents.

Twitter Demographics

The data shown below were collected from the profiles of 83 tweeters 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 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
India 1 <1%
Norway 1 <1%
Brazil 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Spain 1 <1%
Hungary 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 115 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 23%
Researcher 26 21%
Student > Master 16 13%
Student > Bachelor 14 11%
Student > Doctoral Student 8 6%
Other 24 19%
Unknown 8 6%
Readers by discipline Count As %
Engineering 29 23%
Agricultural and Biological Sciences 26 21%
Computer Science 21 17%
Physics and Astronomy 10 8%
Environmental Science 5 4%
Other 21 17%
Unknown 13 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 215. 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 17 March 2021.
All research outputs
#96,601
of 17,609,679 outputs
Outputs from Journal of The Royal Society Interface
#49
of 2,641 outputs
Outputs of similar age
#1,062
of 207,564 outputs
Outputs of similar age from Journal of The Royal Society Interface
#1
of 78 outputs
Altmetric has tracked 17,609,679 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,641 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has done particularly well, scoring higher than 98% of its peers.
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 207,564 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 78 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.