Journal ArticleDOI
Modulation of trail laying in the ant Lasius niger (Hymenoptera: Formicidae) and its role in the collective selection of a food source
TLDR
Simulations of this model showed that the observed modulation of trail laying with respect to food source quality is sufficient in itself to account for the systematic selection of the richer source seen in the experiments.Abstract:
Foragers of the ant Lasius nigerexploiting a 1 Msugar source were found to lay 43 %more trail marks than those exploiting a 0.05 or a 0.1 Msource. The trail laying per forager decreased during the course of individual recruitment episodes, and the mean lifetime of the trail pheromone was estimated to be 47 min. A mathematical function describing the probability that a forager chooses one of two paths in relation to the amount of trail pheromone on them closely fitted experimental data. These results were incorporated into a model describing the recruitment dynamics of L. niger.Simulations of this model showed that the observed modulation of trail laying with respect to food source quality is sufficient in itself to account for the systematic selection of the richer source seen in the experiments.read more
Citations
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Journal ArticleDOI
From foraging trails to transport networks: how the quality-distance trade-off shapes network structure.
Valentin Lecheval,Hannah Larson,Dominic D. R. Burns,Samuel Ellis,Scott Powell,Matina C. Donaldson-Matasci,Elva J. H. Robinson +6 more
TL;DR: In this article, a theory for the generation of effective multi-source multi-sink transport networks based on combining exploration and positive reinforcement of best sources is presented, which can explain the structure of complex ant transport networks.
Journal ArticleDOI
Individual and collective choice: parallel prospecting and mining in ants
TL;DR: A mechanism whereby collective co-ordination in the production of social infrastructure can occur in the absence of signalling is discussed.
Journal ArticleDOI
Aircraft technology portfolio optimization using ant colony optimization
TL;DR: Results show that ACO and GAs converge faster and find optima more easily than SA, and thatACO can optimize portfolios with technology incompatibilities without using penalty functions, paving the way for more use of ACO when the number of constraints increases.
Journal ArticleDOI
Ant Colony Optimization Using Common Social Information and Self-Memory
TL;DR: In this paper, the authors introduced the ant system using individual memories (ASIM) aiming to improve the ability to solve TSP while maintaining the diversity of the behavior of each ant.
References
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Journal ArticleDOI
The self-organizing exploratory pattern of the argentine ant
TL;DR: A minimal model shows how the exploratory pattern may be generated by the individual workers' simple trail-laying and -following behavior, illustrating how complex collective structures in insect colonies may be based on self-organization.
Journal ArticleDOI
Collective decision-making in honey bees: how colonies choose among nectar sources
TL;DR: It is suggested that honey bee colonies possess decentralized decision-making because it combines effectiveness with simplicity of communication and computation within a colony.
Journal ArticleDOI
Trails and U-turns in the Selection of a Path by the Ant Lasius niger
TL;DR: The selection of the path is shown to be a collective process whereby trail laying and following amplifies small initial differences in the traffic on each path caused by these three mechanisms, and the foragers show no significant tendency to follow the path they used previously.
Journal ArticleDOI
Collective decision making through food recruitment
TL;DR: A series of experiments shows how the andLasius niger uses its trail recruitment system to select between two food sources, simultaneously presented with to 1M sucrose solution and when offered a 1M solution together with a 0.1M solution.
Journal ArticleDOI
A model of collective nectar source selection by honey bees : self-organization through simple rules
Scott Camazine,James Sneyd +1 more
TL;DR: In this article, the authors present a model that describes the honey bee colony's decision-making process, which consists of a system of non-linear differential equations describing the activity of the foraging bees.