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A genetic mission planner for solving temporal multi-agent problems with concurrent tasks
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5224-8302
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5832-5452
2017 (English)In: Lecture Notes in Computer Science, vol. 10386, Springer Verlag , 2017, p. 481-493Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a centralized mission planner is presented. The planner employs a genetic algorithm for the optimization of the temporal planning problem. With the knowledge of agents’ specification and capabilities, as well as constraints and parameters for each task, the planner can produce plans that utilize multi-agent tasks, concurrency on agent level, and heterogeneous agents. Numerous optimization criteria that can be of use to the mission operator are tested on the same mission data set. Promising results and effectiveness of this approach are presented in the case study section. 

Place, publisher, year, edition, pages
Springer Verlag , 2017. p. 481-493
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10386
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-36246DOI: 10.1007/978-3-319-61833-3_51ISI: 000439782400051Scopus ID: 2-s2.0-85026782436ISBN: 9783319618326 OAI: oai:DiVA.org:mdh-36246DiVA, id: diva2:1133935
Conference
8th International Conference on Swarm Intelligence, ICSI 2017; Fukuoka; Japan; 27 July 2017 through 1 August 2017
Available from: 2017-08-17 Created: 2017-08-17 Last updated: 2018-08-17Bibliographically approved

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Çürüklü, BaranEkström, Mikael

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf