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The importance of information flow regulation in preferentially foraging robot swarms

The importance of information flow regulation in preferentially foraging robot swarms
The importance of information flow regulation in preferentially foraging robot swarms
Instead of committing to the first source of reward that it discovers, an agent engaged in "preferential foraging" continues to choose between different reward sources in order to maximise its foraging efficiency. In this paper, the effect of preferential source selection on the performance of robot swarms with different recruitment strategies is studied. The swarms are tasked with foraging from multiple sources in dynamic environments where worksite locations change periodically and thus need to be re-discovered. Analysis indicates that preferential foraging leads to a more even exploitation of resources and a more efficient exploration of the environment provided that information
flow among robots, that results from recruitment, is regulated. On the other hand, preferential selection acts as a strong positive feedback mechanism for favouring the most popular reward source when robots exchange information rapidly in a small designated area, preventing the swarm from foraging efficiently and from responding to changes.
Springer
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Dorigo, Marco
Birattari, Mauro
Blum, Christian
Christensen, Anders L.
Reina, Andreagiovanni
Trianni, Vito
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Dorigo, Marco
Birattari, Mauro
Blum, Christian
Christensen, Anders L.
Reina, Andreagiovanni
Trianni, Vito

Pitonakova, Lenka, Crowder, Richard and Bullock, Seth (2018) The importance of information flow regulation in preferentially foraging robot swarms. Dorigo, Marco, Birattari, Mauro, Blum, Christian, Christensen, Anders L., Reina, Andreagiovanni and Trianni, Vito (eds.) In Swarm Intelligence: 11th International Conference, ANTS 2018, Rome, Italy, October 29–31, 2018, Proceedings. Springer..

Record type: Conference or Workshop Item (Paper)

Abstract

Instead of committing to the first source of reward that it discovers, an agent engaged in "preferential foraging" continues to choose between different reward sources in order to maximise its foraging efficiency. In this paper, the effect of preferential source selection on the performance of robot swarms with different recruitment strategies is studied. The swarms are tasked with foraging from multiple sources in dynamic environments where worksite locations change periodically and thus need to be re-discovered. Analysis indicates that preferential foraging leads to a more even exploitation of resources and a more efficient exploration of the environment provided that information
flow among robots, that results from recruitment, is regulated. On the other hand, preferential selection acts as a strong positive feedback mechanism for favouring the most popular reward source when robots exchange information rapidly in a small designated area, preventing the swarm from foraging efficiently and from responding to changes.

Text Pitonakova_preferentialForaging - Accepted Manuscript
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More information

Accepted/In Press date: 2 July 2018
e-pub ahead of print date: 6 December 2018

Identifiers

Local EPrints ID: 423165
URI: https://eprints.soton.ac.uk/id/eprint/423165
PURE UUID: 6d432673-5368-49b3-99c3-f1ba186c7524
ORCID for Lenka Pitonakova: ORCID iD orcid.org/0000-0003-3633-7302

Catalogue record

Date deposited: 19 Sep 2018 16:30
Last modified: 05 Oct 2018 11:33

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Contributors

Author: Lenka Pitonakova ORCID iD
Author: Richard Crowder
Author: Seth Bullock
Editor: Marco Dorigo
Editor: Mauro Birattari
Editor: Christian Blum
Editor: Anders L. Christensen
Editor: Andreagiovanni Reina
Editor: Vito Trianni

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