Logo des Repositoriums
 

The RACE Project

dc.contributor.authorHertzberg, Joachim
dc.contributor.authorZhang, Jianwei
dc.contributor.authorZhang, Liwei
dc.contributor.authorRockel, Sebastian
dc.contributor.authorNeumann, Bernd
dc.contributor.authorLehmann, Jos
dc.contributor.authorDubba, Krishna S. R.
dc.contributor.authorCohn, Anthony G.
dc.contributor.authorSaffiotti, Alessandro
dc.contributor.authorPecora, Federico
dc.contributor.authorMansouri, Masoumeh
dc.contributor.authorKonečný, Štefan
dc.contributor.authorGünther, Martin
dc.contributor.authorStock, Sebastian
dc.contributor.authorLopes, Luis Seabra
dc.contributor.authorOliveira, Miguel
dc.contributor.authorLim, Gi Hyun
dc.contributor.authorKasaei, Hamidreza
dc.contributor.authorMokhtari, Vahid
dc.contributor.authorHotz, Lothar
dc.contributor.authorBohlken, Wilfried
dc.date.accessioned2018-01-08T09:17:26Z
dc.date.available2018-01-08T09:17:26Z
dc.date.issued2014
dc.description.abstractThis paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.
dc.identifier.pissn1610-1987
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/11426
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 28, No. 4
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.titleThe RACE Project
dc.typeText/Journal Article
gi.citation.endPage304
gi.citation.startPage297

Dateien