Publikation: Guerrilla Performance Analysis for Robot Swarms : Degrees of Collaboration and Chains of Interference Events
Lade...
Dateien
Datum
2020
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
DORIGO, Marco, ed., Thomas STÜTZLE, ed., Heiko HAMANN, ed. and others. Swarm Intelligence : 12th International Conference, ANTS 2020, Proceedings. Cham: Springer, 2020, pp. 134-147. Lecture Notes in Computer Science. 12421. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-60375-5. Available under: doi: 10.1007/978-3-030-60376-2_11
Zusammenfassung
Scalability is a key feature of swarm robotics. Hence, measuring performance depending on swarm size is important to check the validity of the design. Performance diagrams have generic qualities across many different application scenarios. We summarize these findings and condense them in a practical performance analysis guide for swarm robotics. We introduce three general classes of performance: linear increase, saturation, and increase/decrease. As the performance diagrams may contain rich information about underlying processes, such as the degree of collaboration and chains of interference events in crowded situations, we discuss options for quickly devising hypotheses about the underlying robot behaviors. The validity of our performance analysis guide is then made plausible in a number of simple examples based on models and simulations.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
Swarm Intelligence : 12th International Conference, ANTS 2020, 26. Okt. 2020 - 28. Okt. 2020, Barcelona, Spain
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
HAMANN, Heiko, Till AUST, Andreagiovanni REINA, 2020. Guerrilla Performance Analysis for Robot Swarms : Degrees of Collaboration and Chains of Interference Events. Swarm Intelligence : 12th International Conference, ANTS 2020. Barcelona, Spain, 26. Okt. 2020 - 28. Okt. 2020. In: DORIGO, Marco, ed., Thomas STÜTZLE, ed., Heiko HAMANN, ed. and others. Swarm Intelligence : 12th International Conference, ANTS 2020, Proceedings. Cham: Springer, 2020, pp. 134-147. Lecture Notes in Computer Science. 12421. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-60375-5. Available under: doi: 10.1007/978-3-030-60376-2_11BibTex
@inproceedings{Hamann2020Guerr-59738,
year={2020},
doi={10.1007/978-3-030-60376-2_11},
title={Guerrilla Performance Analysis for Robot Swarms : Degrees of Collaboration and Chains of Interference Events},
number={12421},
isbn={978-3-030-60375-5},
issn={0302-9743},
publisher={Springer},
address={Cham},
series={Lecture Notes in Computer Science},
booktitle={Swarm Intelligence : 12th International Conference, ANTS 2020, Proceedings},
pages={134--147},
editor={Dorigo, Marco and Stützle, Thomas and Hamann, Heiko},
author={Hamann, Heiko and Aust, Till and Reina, Andreagiovanni}
}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/123456789/59738">
<dc:contributor>Reina, Andreagiovanni</dc:contributor>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/59738"/>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:creator>Aust, Till</dc:creator>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dc:contributor>Aust, Till</dc:contributor>
<dcterms:title>Guerrilla Performance Analysis for Robot Swarms : Degrees of Collaboration and Chains of Interference Events</dcterms:title>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-16T14:37:07Z</dcterms:available>
<dc:creator>Hamann, Heiko</dc:creator>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:creator>Reina, Andreagiovanni</dc:creator>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/59738/1/Hamann_2-v0a841ubzvqf2.pdf"/>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-16T14:37:07Z</dc:date>
<dcterms:issued>2020</dcterms:issued>
<dcterms:abstract xml:lang="eng">Scalability is a key feature of swarm robotics. Hence, measuring performance depending on swarm size is important to check the validity of the design. Performance diagrams have generic qualities across many different application scenarios. We summarize these findings and condense them in a practical performance analysis guide for swarm robotics. We introduce three general classes of performance: linear increase, saturation, and increase/decrease. As the performance diagrams may contain rich information about underlying processes, such as the degree of collaboration and chains of interference events in crowded situations, we discuss options for quickly devising hypotheses about the underlying robot behaviors. The validity of our performance analysis guide is then made plausible in a number of simple examples based on models and simulations.</dcterms:abstract>
<dc:language>eng</dc:language>
<dc:contributor>Hamann, Heiko</dc:contributor>
<dc:rights>terms-of-use</dc:rights>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/59738/1/Hamann_2-v0a841ubzvqf2.pdf"/>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
