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dc.date.accessioned 2004-05-17T18:44:11Z
dc.date.available 2004-05-17T03:00:00Z
dc.date.issued 2003-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9461
dc.description.abstract Options have been shown to be a key step in extending reinforcement learning beyond low-level reactionary systems to higher-level, planning systems. Most of the options research involves hand-crafted options; there has been only very limited work in the automated discovery of options. We extend early work in automated option discovery with a flexible and robust method. en
dc.format.extent 9-14 es
dc.language en es
dc.subject Learning es
dc.subject subgoal discovery en
dc.title Improved automatic discovery of subgoals for options in hierarchical en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct03-2.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Kretchmar, R. Matthew es
sedici.creator.person Feil, Todd es
sedici.creator.person Bansal, Rohit es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000252 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 3, no. 2 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)