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dc.contributorThe Pennsylvania State University CiteSeerX Archives
dc.contributor.authorGregory Kuhlmann
dc.contributor.authorPeter Stone
dc.contributor.authorRaymond Mooney
dc.contributor.authorJude Shavlik
dc.date.accessioned2019-10-28T20:21:13Z
dc.date.available2019-10-28T20:21:13Z
dc.date.created2018-09-05 00:44
dc.date.issued2009-04-18
dc.identifieroai:CiteSeerX.psu:10.1.1.10.4612
dc.identifierhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.4612
dc.identifier.urihttp://hdl.handle.net/20.500.12424/2486342
dc.description.abstractWe describe our current efforts towards creating a reinforcement learner that learns both from reinforcements provided by its environment and from human-generated advice. Our research involves two complementary components: (a) mapping advice expressed in English to a formal advice language and (b) using advice expressed in a formal notation in a reinforcement learner. We use a subtask of the challenging RoboCup simulated soccer task (Noda et al. 1998) as our testbed.
dc.format.mediumapplication/postscript
dc.languageen
dc.language.isoeng
dc.rightsMetadata may be used without restrictions as long as the oai identifier remains attached to it.
dc.titleInitial Results in RoboCup Soccer
dc.typetext
ge.collectioncodeOAIDATA
ge.dataimportlabelOAI metadata object
ge.identifier.legacyglobethics:15135058
ge.identifier.permalinkhttps://www.globethics.net/gel/15135058
ge.lastmodificationdate2018-09-05 00:44
ge.lastmodificationuseradmin@pointsoftware.ch (import)
ge.submissions0
ge.oai.exportid149801
ge.oai.repositoryid54
ge.oai.streamid2
ge.setnameGlobeEthicsLib
ge.setspecglobeethicslib
ge.linkhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.4612
ge.linkhttp://www.cs.utexas.edu/users/ml/papers/advice-aaai-wkshp-04.ps.gz


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