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A Game-Theoretical Winner and Loser Model of Dominance Hierarchy Formation

Overview of attention for article published in Bulletin of Mathematical Biology, June 2016
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Title
A Game-Theoretical Winner and Loser Model of Dominance Hierarchy Formation
Published in
Bulletin of Mathematical Biology, June 2016
DOI 10.1007/s11538-016-0186-9
Pubmed ID
Authors

Klodeta Kura, Mark Broom, Anne Kandler

Abstract

Many animals spend large parts of their lives in groups. Within such groups, they need to find efficient ways of dividing available resources between them. This is often achieved by means of a dominance hierarchy, which in its most extreme linear form allocates a strict priority order to the individuals. Once a hierarchy is formed, it is often stable over long periods, but the formation of hierarchies among individuals with little or no knowledge of each other can involve aggressive contests. The outcome of such contests can have significant effects on later contests, with previous winners more likely to win (winner effects) and previous losers more likely to lose (loser effects). This scenario has been modelled by a number of authors, in particular by Dugatkin. In his model, individuals engage in aggressive contests if the assessment of their fighting ability relative to their opponent is above a threshold [Formula: see text]. Here we present a model where each individual can choose its own value [Formula: see text]. This enables us to address questions such as how aggressive should individuals be in order to take up one of the first places in the hierarchy? We find that a unique strategy evolves, as opposed to a mixture of strategies. Thus, in any scenario there exists a unique best level of aggression, and individuals should not switch between strategies. We find that for optimal strategy choice, the hierarchy forms quickly, after which there are no mutually aggressive contests.

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Mendeley readers

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The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 23%
Researcher 6 23%
Lecturer 2 8%
Student > Master 2 8%
Student > Ph. D. Student 2 8%
Other 3 12%
Unknown 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 35%
Computer Science 2 8%
Medicine and Dentistry 2 8%
Social Sciences 2 8%
Psychology 1 4%
Other 2 8%
Unknown 8 31%
Attention Score in Context

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 2016.
All research outputs
#20,337,210
of 22,882,389 outputs
Outputs from Bulletin of Mathematical Biology
#1,001
of 1,101 outputs
Outputs of similar age
#305,331
of 352,730 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#8
of 12 outputs
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So far Altmetric has tracked 1,101 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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