Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105485
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dc.contributorDepartment of Computingen_US
dc.creatorAziz, Hen_US
dc.creatorChan, Hen_US
dc.creatorCseh, Áen_US
dc.creatorLi, Ben_US
dc.creatorRamezani, Fen_US
dc.creatorWang, Cen_US
dc.date.accessioned2024-04-15T07:34:38Z-
dc.date.available2024-04-15T07:34:38Z-
dc.identifier.isbn978-1-4503-8307-3en_US
dc.identifier.urihttp://hdl.handle.net/10397/105485-
dc.description20th International Conference on Autonomous Agents and Multiagent Systems, 3-7 May 2021, Virtualen_US
dc.language.isoenen_US
dc.publisherAssociation for Computing Machineryen_US
dc.rightsCopyright © 2021 by International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)en_US
dc.rightsPosted with permission of the publisher.en_US
dc.rightsThe AAMAS papers are archived to the ACM Digital Library (https://dl.acm.org/doi/proceedings/10.5555/3463952) and to the IFAAMAS repository (https://www.ifaamas.org/Proceedings/aamas2021/).en_US
dc.subjectComplexityen_US
dc.subjectMatchingen_US
dc.subjectRobot-task allocationen_US
dc.titleMulti-robot task allocation : complexity and approximationen_US
dc.typeConference Paperen_US
dc.identifier.spage133en_US
dc.identifier.epage141en_US
dc.identifier.doi10.5555/3463952.3463974en_US
dcterms.abstractMulti-robot task allocation is one of the most fundamental classes of problems in robotics and is crucial for various real-world robotic applications such as search, rescue and area exploration. We consider the Single-Task robots and Multi-Robot tasks Instantaneous Assignment (ST-MR-IA) setting where each task requires at least a certain number of robots and each robot can work on at most one task and incurs an operational cost for each task. Our aim is to consider a natural computational problem of allocating robots to complete the maximum number of tasks subject to budget constraints. We consider budget constraints of three different kinds: (1) total budget, (2) task budget, and (3) robot budget. We provide a detailed complexity analysis including results on approximations as well as polynomial-time algorithms for the general setting and important restricted settings.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems, p. 133-141. Richland, SC : International Foundation for Autonomous Agents and Multiagent Systems, 2021en_US
dcterms.issued2021-
dc.relation.ispartofbookProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systemsen_US
dc.relation.conferenceInternational Conference on Autonomous Agents and Multiagent Systems [AAMAS]en_US
dc.description.validate202402 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberCOMP-0138-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS50798503-
dc.description.oaCategoryPublisher permissionen_US
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