Collective decision with 100 Kilobots: speed versus accuracy in binary discrimination problems

Achieving fast and accurate collective decisions with a large number of simple agents without relying on a central planning unit or on global communication is essential for developing complex collective behaviors. In this paper, we investigate the speed versus accuracy trade-off in collective decisi...

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Bibliographic Details
Published inAutonomous agents and multi-agent systems Vol. 30; no. 3; pp. 553 - 580
Main Authors Valentini, Gabriele, Ferrante, Eliseo, Hamann, Heiko, Dorigo, Marco
Format Journal Article
LanguageEnglish
Published New York Springer US 01.05.2016
Springer Verlag
Subjects
Adaptation and Self-Organizing Systems
Artificial Intelligence
Computational Complexity
Computer Science
Computer Systems Organization and Communication Networks
Machine Learning
Multiagent Systems
Nonlinear Sciences
Robotics
Software Engineering/Programming and Operating Systems
User Interfaces and Human Computer Interaction
Kilobot
Collective decision-making
Swarm robotics
Ordinary differential equations
Majority rule
Voter model
Chemical reaction network
Gillespie algorithm
Self-organization
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Summary:Achieving fast and accurate collective decisions with a large number of simple agents without relying on a central planning unit or on global communication is essential for developing complex collective behaviors. In this paper, we investigate the speed versus accuracy trade-off in collective decision-making in the context of a binary discrimination problem—i.e., how a swarm can collectively determine the best of two options. We describe a novel, fully distributed collective decision-making strategy that only requires agents with minimal capabilities and is faster than previous approaches. We evaluate our strategy experimentally, using a swarm of 100 Kilobots, and we study it theoretically, using both continuum and finite-size models. We find that the main factor affecting the speed versus accuracy trade-off of our strategy is the agents’ neighborhood size—i.e., the number of agents with whom the current opinion of each agent is shared. The proposed strategy and the associated theoretical framework can be used to design swarms that take collective decisions at a given level of speed and/or accuracy.
ISSN:1387-2532
1573-7454
DOI:10.1007/s10458-015-9323-3