ArticleBulletin of mathematical biology2016
A Game-Theoretical Winner and Loser Model of Dominance Hierarchy Formation.
Article in Bulletin of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Bayesian updating for self-assessment explains social dominance and winner-loser effects.Animal behaviour · 2025Article
- Neural circuit mechanisms underlying dominance traits and social competition.Biophysics reviews · 2025Article
- Postsynaptic lncRNA Sera/Pkm2 pathway orchestrates the transition from social competition to rank by remodeling the neural ensemble in mPFC.Cell discovery · 2024Article
- Winner-loser effects improve social network efficiency between competitors with equal resource holding power.Scientific reports · 2023Article
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3 authors.
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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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