Brood sorting by ants: distributing the workload over the work-surface

Franks, NR; Sendova‐Franks, Ana B.

doi:10.1007/bf00173947

Cited by 138 publications

(112 citation statements)

References 13 publications

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“…Other experiments on the ant Phaidole Pallidula are also reported in Deneubourg et al [16]. Brood sorting is observed by Franks and Sendova-Franks [27] in the ant Leptothorax Unifasciatus. Workers of this species gather the larvae according to their size.…”

Section: Ant-based Clustering In the Literaturesupporting

confidence: 57%

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Ant-based Clustering Algorithms: A Brief Survey

Jafar¹,

Sivakumar²

2010

IJCTE

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Abstract-Ant-based clustering is a biologically inspired data clustering technique. Clustering task aims at the unsupervised classification of patterns in different groups. Clustering problem has been approached from different disciplines during last years. In recent years, many algorithms have been developed for solving numerical and combinatorial optimization problems. Most promising among them are swarm intelligence algorithms. Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering techniques. These algorithms have recently been shown to produce good results in a wide variety of real-world applications. During the last five years, research on and with the ant-based clustering algorithms has reached a very promising state. In this paper, a brief survey on ant-based clustering algorithms is described. We also present some applications of ant-based clustering algorithms.

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Section: Ant-based Clustering In the Literaturesupporting

confidence: 57%

“…Workers of this species gather the larvae according to their size. Franks and Sendova-Franks [27] have intensively analyzed the distribution of brood within the brood cluster.…”

Section: Ant-based Clustering In the Literaturementioning

confidence: 99%

Ant-based Clustering Algorithms: A Brief Survey

Jafar¹,

Sivakumar²

2010

IJCTE

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“…For example, ants exhibit brood clustering (Franks and Sendova-Franks 1992) and termites are able to deposit mud to build complex nests (Grassé 1959). Insects usually exploit natural occurring gradients, such as temperature gradients, or pheromones gradients to tackle this tasks.…”

Section: Source Of Inspirationmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.

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“…Their biological inspiration is reflected in the explicit analogies that are drawn to living biological systems. For example, the suggestion is made on the basis of the robot sorting studies that the brood sorting which ants undertake (Franks and Sendova-Franks, 1992) might be accomplished by similar mechanisms (Holland and Melhuish, 1999).…”

Section: Original Swarm Roboticsmentioning

confidence: 99%

Swarm robotics and minimalism

Sharkey

2007

Connection Science

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Swarm Robotics (SR) is closely related to Swarm Intelligence, and both were initially inspired by studies of social insects. Their guiding principles are based on their biological inspiration and take the form of an emphasis on decentralised local control and communication. Earlier studies went a step further in emphasising the use of simple reactive robots that only communicate indirectly through the environment. More recently SR studies have moved beyond these constraints to explore the use of non-reactive robots that communicate directly, and that can learn and represent their environment. There is no clear agreement in the literature about how far such extensions of the original principles could go. Should there be any limitations on the individual abilities of the robots used in SR studies? Should knowledge of the capabilities of social insects lead to constraints on the capabilities of individual robots in SR studies? There is a lack of explicit discussion of such questions and researchers have adopted a variety of constraints for a variety of reasons. A simple taxonomy of swarm robotics is presented here with the aim of addressing and clarifying these questions. The taxonomy distinguishes sub-areas of SR based on the emphases and justifications for minimalism and individual simplicity.

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Brood sorting by ants: distributing the workload over the work-surface

Cited by 138 publications

References 13 publications

Ant-based Clustering Algorithms: A Brief Survey

Ant-based Clustering Algorithms: A Brief Survey

Swarm robotics: a review from the swarm engineering perspective

Swarm robotics and minimalism

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