Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/4458Registo completo
| Campo DC | Valor | Idioma |
|---|---|---|
| dc.contributor.author | Erlhagen, Wolfram | - |
| dc.contributor.author | Mukovskiy, Albert | - |
| dc.contributor.author | Bicho, E. | - |
| dc.contributor.author | Panin, Giorgio | - |
| dc.contributor.author | Kiss, Casba | - |
| dc.contributor.author | Knoll, Alois | - |
| dc.contributor.author | Van Schie, Hein | - |
| dc.contributor.author | Bekkering, Harold | - |
| dc.date.accessioned | 2006-02-17T17:07:05Z | - |
| dc.date.available | 2006-02-17T17:07:05Z | - |
| dc.date.issued | 2005 | - |
| dc.identifier.citation | DUCH, W. [et al.], ed. – “Artificial neural networks : formal models and their applications - ICANN 2005 : 15th International Conference, Warsaw, Poland, September 11-15, 2005 : proceedings”. Berlin [etc.] : Springer, cop. 2005. ISBN 3-540-28755-8. p. 261-268. | eng |
| dc.identifier.isbn | 3-540-28755-8 | - |
| dc.identifier.issn | 0302-9743 | por |
| dc.identifier.uri | https://hdl.handle.net/1822/4458 | - |
| dc.description.abstract | We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is biologically inspired as it reflects recent experimental findings in action observation/execution studies. We test its functionality in variations of an imitation paradigm in which the artefact has to reproduce the observed or inferred end state of a grasping-placing sequence displayed by a human model. | eng |
| dc.description.sponsorship | European Commission (EC) - IST-2000-29686. | por |
| dc.language.iso | eng | eng |
| dc.publisher | Springer | eng |
| dc.rights | openAccess | eng |
| dc.subject | Imitation learning | eng |
| dc.subject | Robotics | eng |
| dc.subject | Dynamic field model | eng |
| dc.subject | Action understanding | eng |
| dc.title | Action understanding and imitation learning in a robot-human task | eng |
| dc.type | conferencePaper | eng |
| dc.peerreviewed | yes | eng |
| oaire.citationStartPage | 261 | por |
| oaire.citationEndPage | 268 | por |
| oaire.citationVolume | 3696 | por |
| dc.identifier.doi | 10.1007/11550822_42 | por |
| dc.subject.wos | Science & Technology | por |
| sdum.journal | Lecture Notes in Computer Science | por |
| sdum.conferencePublication | ARTIFICIAL NEURAL NETWORKS: BIOLOGICAL INSPIRATIONS - ICANN 2005, PT 1, PROCEEDINGS | por |
| Aparece nas coleções: | Offmath - Comunicações | |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| 36960261.pdf | Documento principal | 3,82 MB | Adobe PDF | Ver/Abrir |
