Ant algorithms and stigmergy

Dorigo, Marco; Bonabeau, Eric; Théraulaz, Guy

doi:10.1016/s0167-739x(00)00042-x

Cited by 681 publications

(339 citation statements)

References 46 publications

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“…The modifications (chemical trails) are used as a form of communication; this process of stigmergy was first described in Grasse (1959). The concept of stigmergy was used as a basis for agent coordination in techniques such as ant colony optimization (ACO) (Dorigo et al, 2000) and swarm intelligence (SI) (Dorigo et al, 2006). A real-world use of stigmergy in an industrial application is described in Valckenaers et al (2004).…”

Section: Related Workmentioning

confidence: 99%

Investigating the Impact of Communication Quality on Evolving Populations of Artificial Life Agents

Chowdhury¹,

Sklar²

2015

07/20/2015-07/24/2015

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The work presented in this paper examines the relationship between interaction mechanism and heterogeneity in evolutionary multiagent systems. Three interaction mechanisms are explored (stigmergy, broadcast and unicast), in both homogenous and heterogenous populations of artificial agents. A number of different schemes are compared in an experimental environment which concerns agents that evolve to detect, extract and collect resources in a grid-based world. A series of experiments was conducted to analyze the effects of interaction mechanism and population diversity on multiple performance metrics, under various signal transmission qualities. The results show differences in key performance metrics when signal transmission quality degrades, under some experimental conditions. These observations offer an important take-away message for assessing the robustness of systems that may face inconsistent communication network quality, a common problem in today's "wired" real world.

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Section: Related Workmentioning

confidence: 99%

Investigating the Impact of Communication Quality on Evolving Populations of Artificial Life Agents

Chowdhury¹,

Sklar²

2015

07/20/2015-07/24/2015

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“…It is an instance of the broad category of ant algorithms [23]. Ant-based clustering algorithms are based upon the brood sorting behavior of ants.…”

Section: Ant-based Clustering In the Literaturementioning

confidence: 99%

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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“…Individuals do interact to achieve coordination, but they interact indirectly, so that each insect taken separately does not seem to be involved in coordinated, collective behavior". Stigmergy, self-organisation and ant-colony algorithms are the subject of much interest in the computer science community for optimisation and routing problems (Di Caro & Dorigo, 1998;Dorigo, Bonabeau, & Theraulaz, 2000;Schoonderwoerd, Holland, Bruten, & Rothkrantz, 1996). The application of stigmergy is also being explored in the e-learning domain (Dron, 2002;Dron, Boyne, & Mitchell, 2001), albeit not in the area of wayfinding support.…”

Section: Self-organisation and Wayfindingmentioning

confidence: 99%

Swarm-Based Wayfinding Support in Open and Distance Learning

Tattersall

Maderveld

Berg

et al. 2006

Cognitively Informed Systems

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Open and Distance Learning (ODL) gives learners freedom of time, place and pace of study, putting learner self-direction centre-stage. However, increased responsibility should not come at the price of over-burdening or abandonment of learners as they progress along their learning journey. This paper introduces an approach to wayfinding support for distance learners based on self-organisation theory. It describes an architecture which supports the recording, processing and presentation of collective learner behaviour designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The approach is presented as an alternative to methods of achieving adaptation in hypermedia-based learning environments which involve learner modelling.

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Ant algorithms and stigmergy

Cited by 681 publications

References 46 publications

Investigating the Impact of Communication Quality on Evolving Populations of Artificial Life Agents

Investigating the Impact of Communication Quality on Evolving Populations of Artificial Life Agents

Ant-based Clustering Algorithms: A Brief Survey

Swarm-Based Wayfinding Support in Open and Distance Learning

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