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dc.contributor.authorSu, Hsin-Hao
dc.contributor.authorSu, Lili
dc.contributor.authorDornhaus, Anna
dc.contributor.authorLynch, Nancy Ann
dc.date.accessioned2021-11-23T17:20:17Z
dc.date.available2021-11-08T18:01:49Z
dc.date.available2021-11-23T17:20:17Z
dc.date.issued2017
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttps://hdl.handle.net/1721.1/137743.2
dc.description.abstract© Springer International Publishing AG 2017. We study the distributed task allocation problem in multi-agent systems, where each agent selects a task in such a way that, collectively, they achieve a proper global task allocation. In this paper, inspired by specialization on division of labor in ant colonies, we propose several scalable and efficient algorithms to dynamically allocate the agents as the task demands change. The algorithms have their own pros and cons, with respect to (1) how fast they react to dynamic demands change, (2) how many agents need to switch tasks, (3) whether extra agents are needed, and (4) whether they are resilient to faults.en_US
dc.language.isoen
dc.publisherSpringer Natureen_US
dc.relation.isversionof10.1007/978-3-319-69084-1_11en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleAnt-Inspired Dynamic Task Allocation via Gossipingen_US
dc.typeArticleen_US
dc.identifier.citationSu, Hsin-Hao, Su, Lili, Dornhaus, Anna and Lynch, Nancy. 2017. "Ant-Inspired Dynamic Task Allocation via Gossiping."en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-06-13T16:12:15Z
dspace.date.submission2019-06-13T16:12:16Z
mit.metadata.statusPublication Information Neededen_US


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