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Negative Updating Combined with Opinion Pooling in the Best-of-n Problem in Swarm Robotics

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationSwarm Intelligence
Subtitle of host publication11th International Conference, ANTS 2018 Proceedings (Lecture Notes in Computer Science), October 29-31, 2018. Rome, Italy
Publisher or commissioning bodySpringer Nature
ISBN (Electronic)9783030005337
ISBN (Print)9783030005320
DateAccepted/In press - 29 Jun 2018
DatePublished (current) - 25 Oct 2018
EventEleventh International Conference on Swarm Intelligence (ANTS 2018) - Rome, Italy
Duration: 29 Oct 201831 Oct 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Link
ISSN (Print)0302-9743


ConferenceEleventh International Conference on Swarm Intelligence (ANTS 2018)
Internet address


There is a need for effective collective decision making in decentralised multi-agent and robotic systems. This paper introduces a novel approach to the best-of-n decision problem with large n. It utilises negative feedback obtained from direct pairwise comparison of options and evidence preserving opinion pooling. We present agent-based simulation experiments that explore the effects of pool size and the number of options on the speed of consensus. Robotic simulation experiments are then used to investigate the potential of the approach as a method for solving the best-of-n decision problem in swarm robotic applications. Overall, the results suggest that the proposed approach is highly scalable with regards to n.


Eleventh International Conference on Swarm Intelligence (ANTS 2018)

Duration29 Oct 201831 Oct 2018
Web address (URL)
Degree of recognitionInternational event

Event: Conference

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