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dc.contributor.authorShieber, Stuart
dc.contributor.authorMirsky, Reuth
dc.contributor.authorGal, Ya’akov
dc.date.accessioned2020-05-01T16:50:41Z
dc.date.issued2017-04-22
dc.identifierQuick submit: 2018-05-19T17:30:01-0400
dc.identifier.citationReuth Mirsky, Ya'akov (Kobi) Gal, and Stuart M. Shieber. 2017. CRADLE: An Online Plan Recognition Algorithm for Exploratory Domains. ACM Transactions on Intelligent Systems and Technology 8, no. 3: 1-22.en_US
dc.identifier.issn2157-6904en_US
dc.identifier.issn2157-6912en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:42663119*
dc.description.abstractIn exploratory domains, agents’ behaviors include switching between activities, extraneous actions, and mistakes. Such settings are prevalent in real world applications such as interaction with open-ended software, collaborative office assistants, and integrated development environments. Despite the prevalence of such settings in the real world, there is scarce work in formalizing the connection between high-level goals and low-level behavior and inferring the former from the latter in these settings. We present a formal grammar for describing users’ activities in such domains. We describe a new top-down plan recognition algorithm called CRADLE (Cumulative Recognition of Activities and Decreasing Load of Explanations) that uses this grammar to recognize agents’ interactions in exploratory domains. We compare the performance of CRADLE with state-of-the-art plan recognition algorithms in several experimental settings consisting of real and simulated data. Our results show that CRADLE was able to output plans exponentially more quickly than the state-of-the-art without compromising its correctness, as determined by domain experts. Our approach can form the basis of future systems that use plan recognition to provide real-time support to users in a growing class of interesting and challenging domains.en_US
dc.description.sponsorshipEngineering and Applied Sciencesen_US
dc.language.isoen_USen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dash.licenseOAP
dc.subjectTheoretical Computer Scienceen_US
dc.subjectArtificial Intelligenceen_US
dc.titleCRADLE: An Online Plan Recognition Algorithm for Exploratory Domainsen_US
dc.title.alternativeAn Online Plan Recognition Algorithm for Exploratory Domains
dc.typeJournal Articleen_US
dc.date.updated2018-05-19T21:30:03Z
dc.description.versionAccepted Manuscripten_US
dc.relation.journalACM Transactions on Intelligent Systems and Technologyen_US
dash.depositing.authorShieber, Stuart
dc.date.available2017
dc.date.available2020-05-01T16:50:41Z
dc.identifier.doi10.1145/2996200
dc.source.journalACM Trans. Intell. Syst. Technol.
dash.source.volume8;3
dash.source.page1-22
dash.contributor.affiliatedShieber, Stuart


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