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dc.contributor.authorAlissandrakis, A.
dc.contributor.authorNehaniv, C.L.
dc.contributor.authorDautenhahn, K.
dc.date.accessioned2009-10-08T10:23:07Z
dc.date.available2009-10-08T10:23:07Z
dc.date.issued2002
dc.identifier.citationAlissandrakis , A , Nehaniv , C L & Dautenhahn , K 2002 , ' Do as I Do: Correspondences across Different Robotic Embodiments ' , Procs.5th German Workshop on Artificial Life. Lubeck , no. GWAL5 , pp. 143-152 .
dc.identifier.otherPURE: 85167
dc.identifier.otherPURE UUID: c298ae46-65b6-4899-bc33-689a8158653c
dc.identifier.otherdspace: 2299/3936
dc.identifier.urihttp://hdl.handle.net/2299/3936
dc.description.abstractBehaviour matching and imitation serve as fundamental mechanisms for social learning, the development of social skills, and the evolution of cultures. Imitation and observational learning as means for acquiring new behaviours also represent a largely untapped resource for robotics and artificial life - both in the study of “life as it could be” and for applications of biological mechanisms to synthetic worlds. A crucial problem in imitation is the correspondence problem, mapping action sequences of the demonstrator and the imitator agent. This problem becomes particularly obvious when the two agents do not share the same embodiment and affordances. This paper describes work-in-progress using the general imitating mechanism ALICE (Action Learning for Imitation via Correspondences between Embodiments), trying to find solutions for the correspondence problem between different configurations of robotic arms.en
dc.language.isoeng
dc.relation.ispartofProcs.5th German Workshop on Artificial Life. Lubeck
dc.rightsOpen
dc.titleDo as I Do: Correspondences across Different Robotic Embodimentsen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
dc.relation.schoolSchool of Computer Science
dcterms.dateAccepted2002
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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