| dc.contributor.author | Besold, Tarek | |
| dc.contributor.author | Hernández-Orallo, José | |
| dc.contributor.author | Schmid, Ute | |
| dc.date | 2015-08-01 | |
| dc.date.accessioned | 2018-01-08T09:17:54Z | |
| dc.date.available | 2018-01-08T09:17:54Z | |
| dc.date.issued | 2015 | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/11478 | |
| dc.description.abstract | In recent years the number of research projects on computer programs solving human intelligence problems in artificial intelligence (AI), artificial general intelligence, as well as in Cognitive Modelling, has significantly grown. One reason could be the interest of such problems as benchmarks for AI algorithms. Another, more fundamental, motivation behind this area of research might be the (implicit) assumption that a computer program that successfully can solve human intelligence problems has human-level intelligence and vice versa. This paper analyses this assumption. | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 29, No. 3 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Cognitive modelling | |
| dc.subject | Intelligence tests | |
| dc.subject | Psychometric AI | |
| dc.subject | Strong AI | |
| dc.title | Can Machine Intelligence be Measured in the Same Way as Human intelligence? | |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 291-297 | |
| gi.identifier.doi | 10.1007/s13218-015-0361-4 | |
