Derivation of a Micro-Macro Link for Collective Decision-Making Systems : Uncover Network Features Based on Drift Measurements

Hamann, Heiko; Valentini, Gabriele; Khaluf, Yara; Dorigo, Marco

Derivation of a Micro-Macro Link for Collective Decision-Making Systems : Uncover Network Features Based on Drift Measurements

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2014

Autor:innen

Hamann, Heiko

Valentini, Gabriele

Khaluf, Yara

Dorigo, Marco

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

Parallel Problem Solving from Nature : PPSN XIII, 13th International Conference, Proceedings / Bartz-Beielstein, Thomas; Branke, Jürgen; Filipič, Bogdan et al. (Hrsg.). - Cham : Springer, 2014. - (Lecture Notes in Computer Science, LNCS ; 8672). - S. 181-190. - ISSN 0302-9743. - eISSN 1611-3349. - ISBN 978-3-319-10761-5

Zusammenfassung

Relating microscopic features (individual level) to macroscopic features (swarm level) of self-organizing collective systems is challenging. In this paper, we report the mathematical derivation of a macroscopic model starting from a microscopic one for the example of collective decision-making. The collective system is based on the application of a majority rule over groups of variable size which is modeled by chemical reactions (micro-model). From an approximated master equation we derive the drift term of a stochastic differential equation (macro-model) which is applied to predict the expected swarm behavior. We give a recursive definition of the polynomials defining this drift term. Our results are validated by Gillespie simulations and simulations of the locust alignment.

Fachgebiet (DDC)

004 Informatik

Schlagwörter

Master Equation, Reaction Schema, Majority Rule, Neighborhood Size, Markov Chain Monte Carlo Method

Konferenz

Parallel Problem Solving from Nature - PPSN XIII, 13th International Conference, 13. Sep. 2014 - 17. Sep. 2014, Ljubljana, Slovenia

Zitieren

ISO 690

HAMANN, Heiko, Gabriele VALENTINI, Yara KHALUF, Marco DORIGO, 2014. Derivation of a Micro-Macro Link for Collective Decision-Making Systems : Uncover Network Features Based on Drift Measurements. Parallel Problem Solving from Nature - PPSN XIII, 13th International Conference. Ljubljana, Slovenia, 13. Sep. 2014 - 17. Sep. 2014. In: BARTZ-BEIELSTEIN, Thomas, ed., Jürgen BRANKE, ed., Bogdan FILIPIČ, ed. and others. Parallel Problem Solving from Nature : PPSN XIII, 13th International Conference, Proceedings. Cham:Springer, pp. 181-190. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-10761-5. Available under: doi: 10.1007/978-3-319-10762-2_18

BibTex

@inproceedings{Hamann2014Deriv-59893,
  year={2014},
  doi={10.1007/978-3-319-10762-2_18},
  title={Derivation of a Micro-Macro Link for Collective Decision-Making Systems : Uncover Network Features Based on Drift Measurements},
  number={8672},
  isbn={978-3-319-10761-5},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science, LNCS},
  booktitle={Parallel Problem Solving from Nature : PPSN XIII, 13th International Conference, Proceedings},
  pages={181--190},
  editor={Bartz-Beielstein, Thomas and Branke, Jürgen and Filipič, Bogdan},
  author={Hamann, Heiko and Valentini, Gabriele and Khaluf, Yara 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/123456789/59893">
    <dc:contributor>Dorigo, Marco</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:issued>2014</dcterms:issued>
    <dc:creator>Khaluf, Yara</dc:creator>
    <dcterms:title>Derivation of a Micro-Macro Link for Collective Decision-Making Systems : Uncover Network Features Based on Drift Measurements</dcterms:title>
    <dcterms:abstract xml:lang="eng">Relating microscopic features (individual level) to macroscopic features (swarm level) of self-organizing collective systems is challenging. In this paper, we report the mathematical derivation of a macroscopic model starting from a microscopic one for the example of collective decision-making. The collective system is based on the application of a majority rule over groups of variable size which is modeled by chemical reactions (micro-model). From an approximated master equation we derive the drift term of a stochastic differential equation (macro-model) which is applied to predict the expected swarm behavior. We give a recursive definition of the polynomials defining this drift term. Our results are validated by Gillespie simulations and simulations of the locust alignment.</dcterms:abstract>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Dorigo, Marco</dc:creator>
    <dc:contributor>Valentini, Gabriele</dc:contributor>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/59893"/>
    <dc:contributor>Khaluf, Yara</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-23T13:36:45Z</dcterms:available>
    <dc:language>eng</dc:language>
    <dc:creator>Valentini, Gabriele</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Hamann, Heiko</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-23T13:36:45Z</dc:date>
    <dc:contributor>Hamann, Heiko</dc:contributor>
  </rdf:Description>
</rdf:RDF>

Universitätsbibliographie

Nein