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A field-based versus a protocol-based approach for adaptive task assignment
Katholieke University Leuven. (Computer Science)ORCID iD: 0000-0002-1162-0817
Katholieke University Leuven.
Katholieke University Leuven.
2008 (English)In: Autonomous Agents and Multi-Agent Systems, ISSN 1387-2532, E-ISSN 1573-7454, Vol. 17, no 2, p. 288-319Article in journal (Refereed) Published
Abstract [en]

Task assignment in multi-agent systems is a complex coordination problem, in particular in systems that are subject to dynamic and changing operating conditions. To enable agents to deal with dynamism and change, adaptive task assignment approaches are needed. In this paper, we study two approaches for adaptive task assignment that are characteristic for two classical families of task assignment approaches. FiTA is a field-based approach in which tasks emit fields in the environment that guide idle agents to tasks. DynCNET is a protocol-based approach that extends Standard Contract Net (CNET). In DynCNET, agents use explicit negotiation to assign tasks. We compare both approaches in a simulation of an industrial automated transportation system. Our experiences show that: (1) the performance of DynCNET and FiTA are similar, while both outperform CNET; (2) the complexity to engineer DynCNET is similar to FiTA but much more complex than CNET; (3) whereas task assignment with FiTA is an emergent solution, DynCNET specifies the interaction among agents explicitly allowing engineers to reason on the assignment of tasks, (4) FiTA is inherently robust to message loss while DynCNET requires substantial additional support. The tradeoff between (3) and (4) is an important criteria for the selection of an adaptive task assignment approach in practice.

Place, publisher, year, edition, pages
Springer, 2008. Vol. 17, no 2, p. 288-319
Keywords [en]
task assignment, gradient fields, extended contract net protocol, automatic guided vehicles, AGN
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-19360DOI: 10.1007/s10458-008-9037-xOAI: oai:DiVA.org:lnu-19360DiVA, id: diva2:530343
Available from: 2012-06-01 Created: 2012-06-01 Last updated: 2018-01-12Bibliographically approved

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Weyns, Danny

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf