The self-organizing exploratory pattern of the argentine ant

Deneubourg, Jean‐Louis; Aron, Serge; Goss, Simon; Pasteels, Jacques

doi:10.1007/bf01417909

Cited by 736 publications

(533 citation statements)

References 22 publications

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“…Within the literature on social insects, various models of task allocation are still viewed as unrelated because they are used to describe different behaviour. Here we show, for example, that existing models of foraging on different food sources (Seeley et al, 1991) or trail-following in an ant colony exposed to multiple food sources (Deneubourg et al, 1990), are analogous to the simple model presented in the first section.…”

Section: Discussionmentioning

confidence: 72%

“…assessment by a honeybee forager of the quality of its nectar source in Seeley et al 1991) and in part on its interactions with other individuals (e.g. following the trail pheromone laid by another individual in Deneubourg et al 1990).…”

Section: -7653mentioning

confidence: 99%

“…Deneubourg et al, 1986Deneubourg et al, , 1990Deneubourg and Goss, 1989) have investigated models similar to Equation A8 but that have unstable internal equilibria and simultaneously stable boundary equilibria. In these models, a trail's attractiveness to potential recruits increases faster than linearly with the pheromonal concentration on the trail.…”

Section: Alternative 3: Foraging Trails With Non-linear Recruitmentmentioning

confidence: 99%

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Effects of social group size on information transfer and task allocation

1996

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SummarySocial animals exchange information during social interaction. The rate of interaction and, hence, the rate of information exchange, typically changes with density and density may be affected by the size of the social group. We investigate models in which each individual may be engaged in one of several tasks. For example, the different tasks could represent alternative foraging locations exploited by an ant colony. An individual's decision about which task to pursue depends both on environmental stimuli and on interactions among individuals. We examine how group size affects the allocation of individuals among the various tasks. Analysis of the models shows the following. (1) Simple interactions among individuals with limited ability to process information can lead to group behaviour that closely approximates the predictions of evolutionary optimality models, (2) Because per capita rates of social interaction may increase with group size, larger groups may be more efficient than smaller ones at tracking a changing environment, (3) Group behaviour is determined both by each individual's interaction with environmental stimuli and by social exchange of information. To keep these processes in balance across a range of group sizes, organisms are predicted to regulate per capita rates of social interaction and (4) Stochastic models show, at least in some cases, that the results described here occur even in small groups of approximately ten individuals.

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Section: Discussionmentioning

confidence: 72%

Section: -7653mentioning

confidence: 99%

Section: Alternative 3: Foraging Trails With Non-linear Recruitmentmentioning

confidence: 99%

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Effects of social group size on information transfer and task allocation

1996

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“…The ability to find, select and exploit food resources is crucial and goes under the name of foraging (Deneubourg et al 1990;Camazine et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Collective decision-making based on social odometry

Gutiérrez

Campo

Monasterio-Huelin

et al. 2010

Neural Comput & Applic

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In this paper, we propose a swarm intelligence localization strategy in which robots have to locate different resource areas in a bounded arena and forage between them. The robots have no knowledge of the arena dimensions and of the number of resource areas. The strategy is based on peer-to-peer local communication without the need for any central unit. Social Odometry leads to a self-organized path selection. We show how collective decisions lead the robots to choose the closest resource site from a central place. Results are presented with simulated and real robots.

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“…Therefore, over time ants will converge and follow the shortest route within a network of paths. This has been shown by experiments performed by Deneubourg et al [2]. Dorigo et al, inspired by this interesting behaviour of ant colonies, first developed Ant Colony Optimization (ACO) to solve difficult combinatorial optimization problems like the classic travelling salesman problem [1], [8].…”

Section: The Original Ant-miner Classification Algorithmmentioning

confidence: 95%

A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm

Chan

Freitas

2006

Lecture Notes in Computer Science

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Abstract. This work proposes a new rule pruning procedure for Ant-Miner, an Ant Colony algorithm that discovers classification rules in the context of data mining. The performance of Ant-Miner with the new pruning procedure is evaluated and compared with the performance of the original Ant-Miner across several datasets. The results show that the new pruning procedure has a mixed effect on the performance of Ant-Miner. On one hand, overall it tends to decrease the classification accuracy more often than it improves it. On the other hand, the new pruning procedure in general leads to the discovery of classification rules that are considerably shorter, and so simpler (more easily interpretable by the users) than the rules discovered by the original Ant-Miner.

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The self-organizing exploratory pattern of the argentine ant

Abstract: Workers of the Argentine ant,

Cited by 736 publications

References 22 publications

Effects of social group size on information transfer and task allocation

Effects of social group size on information transfer and task allocation

Collective decision-making based on social odometry

A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm

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