Distributed sequential task allocation in foraging swarms

Harry Goldingay; Jort van Mourik

doi:10.1109/SASO.2013.14

Distributed sequential task allocation in foraging swarms

Harry Goldingay
, Jort van Mourik

Research output: Chapter in Book/Published conference output › Conference publication

3 Citations (Scopus)

131 Downloads (Pure)

Abstract

When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication.

Original language	English
Title of host publication	SASO: 2013 IEEE 7th international conference on Self-Adaptive and Self-Organizing Systems
Publisher	IEEE
Pages	149-158
Number of pages	10
ISBN (Print)	978-0-7695-5129-6
DOIs	https://doi.org/10.1109/SASO.2013.14
Publication status	Published - 11 Sept 2013
Event	7th International Conference on Self-Adaptive and Self-Organizing Systems - Philadelphia, PA, United States Duration: 9 Sept 2013 → 13 Sept 2013

Publication series

Name
ISSN (Print)	1949-3673

Conference

Conference	7th International Conference on Self-Adaptive and Self-Organizing Systems
Abbreviated title	SASO 2013
Country/Territory	United States
City	Philadelphia, PA
Period	9/09/13 → 13/09/13

Bibliographical note

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords

self-organizing systems
evolutionary computing
resource allocation
swarm intelligence

Access to Document

10.1109/SASO.2013.14

Distributed sequential task allocation in foraging swarms
© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Accepted author manuscript, 382 KB

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6676502

Cite this

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title = "Distributed sequential task allocation in foraging swarms",

abstract = "When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication.",

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AU - van Mourik, Jort

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AB - When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication.

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Distributed sequential task allocation in foraging swarms

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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