2016
DOI: 10.7554/elife.20185
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A locally-blazed ant trail achieves efficient collective navigation despite limited information

Abstract: Any organism faces sensory and cognitive limitations which may result in maladaptive decisions. Such limitations are prominent in the context of groups where the relevant information at the individual level may not coincide with collective requirements. Here, we study the navigational decisions exhibited by Paratrechina longicornis ants as they cooperatively transport a large food item. These decisions hinge on the perception of individuals which often restricts them from providing the group with reliable dire… Show more

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Cited by 41 publications
(63 citation statements)
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“…Below we introduce two biologically plausible algorithms (Algorithms 1-2) that describe how a turtle ant at a node s chooses which edge to traverse next among possible neighboring edges t 1 , t 2 , ...t n . These algorithms build upon previous linear and non-linear models, respectively, used to analyze ant trail formation in other species, such as Argentine ants [62,63,64] and pharaoh ants [65]. Let w(s, t i ) be the current weight on edge (s, t i ), and let uniform() be a random value drawn uniformly from [0, 1].…”
Section: Two Candidate Distributed Algorithmsmentioning
confidence: 99%
“…Below we introduce two biologically plausible algorithms (Algorithms 1-2) that describe how a turtle ant at a node s chooses which edge to traverse next among possible neighboring edges t 1 , t 2 , ...t n . These algorithms build upon previous linear and non-linear models, respectively, used to analyze ant trail formation in other species, such as Argentine ants [62,63,64] and pharaoh ants [65]. Let w(s, t i ) be the current weight on edge (s, t i ), and let uniform() be a random value drawn uniformly from [0, 1].…”
Section: Two Candidate Distributed Algorithmsmentioning
confidence: 99%
“…On the other hand, when no vertices are excited, i.e., X = ∅, the geodesic-biased walk reduces to the simple random walk on G, and an old result of Lawler [11] gives a uniform polynomial bound (see also [1,6]) for the expected hitting time of E[τ a (b, ∅)] = O(n 3 ). Many of the existing results in the literature [8,7,5] show that the expected hitting time of a fixed target in the geodesic-biased walk, for various graphs G and random choices of the set X of excited vertices, is significantly smaller than Lawler's uniform bound. Motivated by this, we shall investigate how much the geodesic-bias can decrease the hitting time of a fixed target.…”
Section: Introductionmentioning
confidence: 99%
“…Studies have shown how such trails are generated and adapted over time (Reid, 2010;Czaczkes and Heinze, 2015;Fonio, 2016), and even how they can encode polarity towards or away from the nest site (Jackson, 2004). However, we know very little about how ants are able to accurately track these trails.…”
Section: Introductionmentioning
confidence: 99%