Show simple item record

dc.contributor.authorAgostini, Alejandro Gabriel
dc.contributor.authorTorras, Carme
dc.contributor.authorWörgötter, Florentin
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2011-12-01T13:10:46Z
dc.date.available2011-12-01T13:10:46Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationAgostini, A.G.; Torras, C.; Wörgötter , F. Integrating task planning and interactive learning for robots to work in human environments. A: International Joint Conference on Artificial Intelligence. "22nd International Joint Conference on Artificial Intelligence". AAAI Press. Association for the Advancement of Artificial Intelligence, 2011, p. 2386-2391.
dc.identifier.urihttp://hdl.handle.net/2117/14136
dc.description.abstractHuman environments are challenging for robots, which need to be trainable by lay people and learn new behaviours rapidly without disrupting much the ongoing activity. A system that integrates AI techniques for planning and learning is here proposed to satisfy these strong demands. The approach rapidly learns planning operators from few action experiences using a competitive strategy where many alternatives of cause-effect explanations are evaluated in parallel, and the most successful ones are used to generate the operators. The success of a cause-effect explanation is evaluated by a probabilistic estimate that compensates the lack of experience, producing more confident estimations and speeding up the learning in relation to other known estimates. The system operates without task interruption by integrating in the planning-learning loop a human teacher that supports the planner in making decisions. All the mechanisms are integrated and synchronized in the robot using a general decision-making framework. The feasibility and scalability of the architecture are evaluated in two different robot platforms: a Stäubli arm, and the humanoid ARMAR III.
dc.format.extent6 p.
dc.language.isoeng
dc.publisherAAAI Press. Association for the Advancement of Artificial Intelligence
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshHuman-robot interaction
dc.subject.lcshLearning (artificial intelligence)
dc.titleIntegrating task planning and interactive learning for robots to work in human environments
dc.typeConference report
dc.subject.lemacInteracció persona-robot
dc.subject.lemacAprenentatge automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ijcai.org/papers11/Papers/IJCAI11-398.pdf
dc.rights.accessOpen Access
local.identifier.drac5962288
dc.description.versionPostprint (author’s final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/247947/EU/Gardening with a Cognitive System/GARNICS
local.citation.authorAgostini, A.G.; Torras, C.; Wörgötter , F.
local.citation.contributorInternational Joint Conference on Artificial Intelligence
local.citation.publicationName22nd International Joint Conference on Artificial Intelligence
local.citation.startingPage2386
local.citation.endingPage2391


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder