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dc.contributor.authorDantam, Neil
dc.contributor.authorEssa, Irfan
dc.contributor.authorStilman, Mike
dc.date.accessioned2012-04-05T14:59:34Z
dc.date.available2012-04-05T14:59:34Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/1853/43194
dc.description.abstractWe describe several algorithms used for the inference of linguistic robot policies from human demonstration. First, tracking and match objects using the Hungarian Algorithm. Then, we convert Regular Expressions to Nondeterministic Finite Automata (NFA) using the McNaughton-Yamada-Thompson Algorithm. Next, we use Subset Construction to convert to a Deterministic Finite Automaton. Finally, we minimize finite automata using either Hopcroft's Algorithm or Brzozowski's Algorithm.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesGT-GOLEM-2012-002en_US
dc.subjectDeterministic finite automatonen_US
dc.subjectHopcroft's algorithmen_US
dc.subjectHuman demonstrationen_US
dc.subjectHungarian algorithmen_US
dc.subjectMcNaughton-Yamada-Thompsonen_US
dc.subjectNondeterministic finite automataen_US
dc.subjectRobot control policiesen_US
dc.subjectSubset constructionen_US
dc.titleAlgorithms for Linguistic Robot Policy Inference from Demonstration of Assembly Tasksen_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machines


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