Active random walkers simulate trunk trail formation by ants

Biosystems ◽  
1997 ◽  
Vol 41 (3) ◽  
pp. 153-166 ◽  
Author(s):  
Frank Schweitzer ◽  
Kenneth Lao ◽  
Fereydoon Family
2018 ◽  
Vol 98 (5) ◽  
Author(s):  
Giulia Cencetti ◽  
Federico Battiston ◽  
Duccio Fanelli ◽  
Vito Latora

2017 ◽  
Vol 75 (1) ◽  
pp. 36-57
Author(s):  
Endre Csáki ◽  
Antónia Földes ◽  
Pál Révész
Keyword(s):  

1969 ◽  
Vol 101 (2) ◽  
pp. 118-128 ◽  
Author(s):  
G. L. Ayre

AbstractMethods of trail formation and organization of group foraging by the ants Formica obscuriventris Mayr, Myrmica americana Weber, and Crematogaster lineolata (Say) were studied under laboratory conditions. Each species was able to organize group travel to a persistent food source. M. americana and C. lineolata achieved this by using trail pheromones, the former species using these pheromones only to establish the trail and the latter using them in all stages of foraging. F. obscuriventris apparently did not use trail pheromones and each individual learned the route to the food independently.


2013 ◽  
Vol 55 (2) ◽  
pp. 93-108 ◽  
Author(s):  
JACK D. HYWOOD ◽  
KERRY A. LANDMAN

AbstractThere is much interest within the mathematical biology and statistical physics community in converting stochastic agent-based models for random walkers into a partial differential equation description for the average agent density. Here a collection of noninteracting biased random walkers on a one-dimensional lattice is considered. The usual master equation approach requires that two continuum limits, involving three parameters, namely step length, time step and the random walk bias, approach zero in a specific way. We are interested in the case where the two limits are not consistent. New results are obtained using a Fokker–Planck equation and the results are highly dependent on the simulation update schemes. The theoretical results are confirmed with examples. These findings provide insight into the importance of updating schemes to an accurate macroscopic description of stochastic local movement rules in agent-based models when the lattice spacing represents a physical object such as cell diameter.


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