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dc.contributor.authorUnhelkar, Vaibhav Vasant
dc.contributor.authorShah, Julie A.
dc.date.accessioned2016-03-03T16:52:38Z
dc.date.available2016-03-03T16:52:38Z
dc.date.issued2016-02
dc.identifier.urihttp://hdl.handle.net/1721.1/101433
dc.description.abstractCommunication between agents has the potential to improve team performance of collaborative tasks. However, communication is not free in most domains, requiring agents to reason about the costs and benefits of sharing information. In this work, we develop an online, decentralized communication policy, ConTaCT, that enables agents to decide whether or not to communicate during time-critical collaborative tasks in unknown, deterministic environments. Our approach is motivated by real-world applications, including the coordination of disaster response and search and rescue teams. These settings motivate a model structure that explicitly represents the world model as initially unknown but deterministic in nature, and that de-emphasizes uncertainty about action outcomes. Simulated experiments are conducted in which ConTaCT is compared to other multi-agent communication policies, and results indicate that ConTaCT achieves comparable task performance while substantially reducing communication overhead.en_US
dc.language.isoen_US
dc.publisherAssociation for the Advancement of Artificial Intelligenceen_US
dc.relation.isversionofhttp://www.aaai.org/Conferences/AAAI/2016/aaai16accepted-papers.pdfen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceUnhelkaren_US
dc.titleConTaCT: Deciding to Communicate during Time-Critical Collaborative Tasks in Unknown, Deterministic Domainsen_US
dc.typeArticleen_US
dc.identifier.citationUnhelkar, Vaibhav V., and Julie A. Shah. "ConTaCT: Deciding to Communicate during Time-Critical Collaborative Tasks in Unknown, Deterministic Domains." Thirtieth AAAI Conference on Artificial Intelligence (AAAI-2016) (February 2016).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.approverUnhelkar, Vaibhav Vasanten_US
dc.contributor.mitauthorUnhelkar, Vaibhav Vasanten_US
dc.contributor.mitauthorShah, Julie A.en_US
dc.relation.journalProceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-2016)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsUnhelkar, Vaibhav V.; Shah, Julia A.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1338-8107
dc.identifier.orcidhttps://orcid.org/0000-0002-4530-189X
mit.licenseOPEN_ACCESS_POLICYen_US


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