Task transparency in learning by demonstration : gaze, pointing, and dialog

dc.contributor.advisor Thomaz, Andrea L.
dc.contributor.author dePalma, Nicholas Brian en_US
dc.contributor.committeeMember Isbell, Charles
dc.contributor.committeeMember Hogg, David
dc.contributor.committeeMember Essa, Irfan
dc.contributor.committeeMember Rehg, James M.
dc.contributor.department Computing en_US
dc.date.accessioned 2010-09-15T18:44:13Z
dc.date.available 2010-09-15T18:44:13Z
dc.date.issued 2010-07-07 en_US
dc.description.abstract This body of work explores an emerging aspect of human-robot interaction, transparency. Socially guided machine learning has proven that highly immersive robotic behaviors have yielded better results than lesser interactive behaviors for performance and shorter training time. While other work explores this transparency in learning by demonstration using non-verbal cues to point out the importance or preference users may have towards behaviors, my work follows this argument and attempts to extend it by offering cues to the internal task representation. What I show is that task-transparency, or the ability to connect and discuss the task in a fluent way implores the user to shape and correct the learned goal in ways that may be impossible by other present day learning by demonstration methods. Additionally, some participants are shown to prefer task-transparent robots which appear to have the ability of "introspection" in which it can modify the learned goal by other methods than just demonstration. en_US
dc.description.degree M.S. en_US
dc.identifier.uri http://hdl.handle.net/1853/34702
dc.publisher Georgia Institute of Technology en_US
dc.subject LbD en_US
dc.subject Transparency en_US
dc.subject Robotics en_US
dc.subject Symbol grounding en_US
dc.subject Learning en_US
dc.subject Partial order plan en_US
dc.subject Learning by demonstration en_US
dc.subject.lcsh Robots
dc.subject.lcsh Robotics Human factors
dc.subject.lcsh Machine learning
dc.subject.lcsh Artificial intelligence
dc.subject.lcsh Androids
dc.title Task transparency in learning by demonstration : gaze, pointing, and dialog en_US
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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