| dc.contributor.advisor | Downing, Keith | nb_NO |
| dc.contributor.author | Fjær, Dag Henrik | nb_NO |
| dc.contributor.author | Massali, Kjeld Karim Berg | nb_NO |
| dc.date.accessioned | 2014-12-19T13:33:58Z | |
| dc.date.available | 2014-12-19T13:33:58Z | |
| dc.date.created | 2010-09-04 | nb_NO |
| dc.date.issued | 2009 | nb_NO |
| dc.identifier | 348788 | nb_NO |
| dc.identifier | ntnudaim:4648 | nb_NO |
| dc.identifier.uri | http://hdl.handle.net/11250/251352 | |
| dc.description.abstract | This report explores continuous-time recurrent neural networks (CTRNNs) and their utility in the field of adaptive robotics. The networks herein are evolved in a simulated environment and evaluated on a real robot. The evolved CTRNNs are presented with simple cognitive tasks and the results are analyzed in detail. | nb_NO |
| dc.language | eng | nb_NO |
| dc.publisher | Institutt for datateknikk og informasjonsvitenskap | nb_NO |
| dc.subject | ntnudaim | no_NO |
| dc.subject | SIF2 datateknikk | no_NO |
| dc.subject | Intelligente systemer | no_NO |
| dc.title | Adaptive Robotics | nb_NO |
| dc.type | Master thesis | nb_NO |
| dc.source.pagenumber | 85 | nb_NO |
| dc.contributor.department | Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap | nb_NO |
