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Unsupervised Learning of State Representations for Multiple Tasks

Raffin, Antonin and Höfer, Sebastian and Jonschkowski, Rico and Brock, Oliver and Stulp, Freek (2017) Unsupervised Learning of State Representations for Multiple Tasks. In: Unsupervised Learning of State Representations for Multiple Tasks. Workshop on Deep Learning for Action and Interaction, held in conjunction with Neural Information Processing Systems (NIPS), 2017, Long Beach.

Full text not available from this repository.


Item URL in elib:https://elib.dlr.de/116889/
Document Type:Conference or Workshop Item (Speech)
Title:Unsupervised Learning of State Representations for Multiple Tasks
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Raffin, AntoninUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Höfer, SebastianTU Berlin, Robotics and Biology LaboratoryUNSPECIFIEDUNSPECIFIED
Jonschkowski, RicoTU Berlin, Robotics and Biology LaboratoryUNSPECIFIEDUNSPECIFIED
Brock, OliverTU Berlin, Robotics and Biology LaboratoryUNSPECIFIEDUNSPECIFIED
Stulp, FreekUNSPECIFIEDhttps://orcid.org/0000-0001-9555-9517UNSPECIFIED
Date:2017
Journal or Publication Title:Unsupervised Learning of State Representations for Multiple Tasks
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:reinforcement learning, representation learning
Event Title:Workshop on Deep Learning for Action and Interaction, held in conjunction with Neural Information Processing Systems (NIPS)
Event Location:Long Beach
Event Type:Workshop
Event Date:2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Vorhaben Intelligente Mobilität (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Stulp, Freek
Deposited On:08 Dec 2017 17:14
Last Modified:15 Oct 2024 10:23

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