Self-organized collective decision making : the weighted voter model

Valentini, Gabriele; Hamann, Heiko; Dorigo, Marco

Self-organized collective decision making : the weighted voter model

Files

There are no files associated with this item.

Date

2014

Authors

Valentini, Gabriele

Hamann, Heiko

Dorigo, Marco

Publication type

Contribution to a conference collection

Publication status

Published

Published in

AAMAS '14 : Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems / Bazzan, Ana; Huhns, Michael et al. (ed.). - New York, NY : ACM, 2014. - pp. 45-52. - ISBN 978-1-4503-2738-1

Abstract

Collective decision making in self-organized systems is challenging because it relies on local perception and local communication. Globally defined qualities such as consensus time and decision accuracy are both difficult to predict and difficult to guarantee. We present the weighted voter model which implements a self-organized collective decision making process. We provide an ODE model, a master equation model (numerically solved by the Gillespie algorithm), and agent-based simulations of the proposed decision-making strategy. This set of models enables us to investigate the system behavior in the thermodynamic limit and to investigate finite-size effects due to random fluctuations. Based on our results, we give minimum requirements to guarantee consensus on the optimal decision, a minimum swarm size to guarantee a certain accuracy, and we show that the proposed approach scales with system size and is robust to noise.

Subject (DDC)

004 Computer Science

Conference

AAMAS '14 : 2014 international conference on autonomous agents and multi-agent systems, May 5, 2014 - May 9, 2014, Paris, France

Cite This

ISO 690

VALENTINI, Gabriele, Heiko HAMANN, Marco DORIGO, 2014. Self-organized collective decision making : the weighted voter model. AAMAS '14 : 2014 international conference on autonomous agents and multi-agent systems. Paris, France, May 5, 2014 - May 9, 2014. In: BAZZAN, Ana, ed., Michael HUHNS, ed. and others. AAMAS '14 : Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems. New York, NY:ACM, pp. 45-52. ISBN 978-1-4503-2738-1. Available under: doi: 10.5555/2615731.2615742

BibTex

@inproceedings{Valentini2014-05-05Selfo-59911,
  year={2014},
  doi={10.5555/2615731.2615742},
  title={Self-organized collective decision making : the weighted voter model},
  url={https://dl.acm.org/doi/10.5555/2615731.2615742},
  isbn={978-1-4503-2738-1},
  publisher={ACM},
  address={New York, NY},
  booktitle={AAMAS '14 : Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems},
  pages={45--52},
  editor={Bazzan, Ana and Huhns, Michael},
  author={Valentini, Gabriele and Hamann, Heiko and Dorigo, Marco}
}

RDF

<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/59911">
    <dc:creator>Dorigo, Marco</dc:creator>
    <dc:contributor>Dorigo, Marco</dc:contributor>
    <dc:creator>Hamann, Heiko</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-24T10:28:24Z</dc:date>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Valentini, Gabriele</dc:creator>
    <dcterms:issued>2014-05-05</dcterms:issued>
    <dc:contributor>Valentini, Gabriele</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-24T10:28:24Z</dcterms:available>
    <dc:language>eng</dc:language>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:contributor>Hamann, Heiko</dc:contributor>
    <dcterms:title>Self-organized collective decision making : the weighted voter model</dcterms:title>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/59911"/>
    <dcterms:abstract xml:lang="eng">Collective decision making in self-organized systems is challenging because it relies on local perception and local communication. Globally defined qualities such as consensus time and decision accuracy are both difficult to predict and difficult to guarantee. We present the weighted voter model which implements a self-organized collective decision making process. We provide an ODE model, a master equation model (numerically solved by the Gillespie algorithm), and agent-based simulations of the proposed decision-making strategy. This set of models enables us to investigate the system behavior in the thermodynamic limit and to investigate finite-size effects due to random fluctuations. Based on our results, we give minimum requirements to guarantee consensus on the optimal decision, a minimum swarm size to guarantee a certain accuracy, and we show that the proposed approach scales with system size and is robust to noise.</dcterms:abstract>
  </rdf:Description>
</rdf:RDF>

URL of original publication

https://dl.acm.org/doi/10.5555/2615731.2615742

Test date of URL

2023-01-16

Bibliography of Konstanz

No