Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations

Wendelin Böhmer; Jost Tobias Springenberg; Joschka Boedecker; Martin Riedmiller; Klaus Obermayer

doi:10.1007/s13218-015-0356-1

Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations

Wendelin Böhmer, Jost Tobias Springenberg, Joschka Boedecker, Martin Riedmiller, Klaus Obermayer

Research output: Contribution to journal › Article › Scientific › peer-review

Original language	English
Pages (from-to)	353-362
Number of pages	10
Journal	KI - Künstliche Intelligenz
Volume	29
Issue number	4
DOIs	https://doi.org/10.1007/s13218-015-0356-1
Publication status	Published - 2015
Externally published	Yes

Access to Document

10.1007/s13218-015-0356-1

http://www.redaktion.tu-berlin.de/fileadmin/fg215/articles/boehmer15b.pdf

Cite this

Böhmer, W., Springenberg, J. T., Boedecker, J., Riedmiller, M., & Obermayer, K. (2015). Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations. KI - Künstliche Intelligenz, 29(4), 353-362. https://doi.org/10.1007/s13218-015-0356-1

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title = "Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations",

author = "Wendelin B{\"o}hmer and Springenberg, {Jost Tobias} and Joschka Boedecker and Martin Riedmiller and Klaus Obermayer",

year = "2015",

doi = "10.1007/s13218-015-0356-1",

language = "English",

volume = "29",

pages = "353--362",

journal = "KI - K{\"u}nstliche Intelligenz",

issn = "0933-1875",

publisher = "Springer Nature",

number = "4",

}

Böhmer, W, Springenberg, JT, Boedecker, J, Riedmiller, M & Obermayer, K 2015, 'Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations', KI - Künstliche Intelligenz, vol. 29, no. 4, pp. 353-362. https://doi.org/10.1007/s13218-015-0356-1

Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations. / Böhmer, Wendelin; Springenberg, Jost Tobias; Boedecker, Joschka et al.
In: KI - Künstliche Intelligenz, Vol. 29, No. 4, 2015, p. 353-362.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Autonomous Learning of State Representations for Control

T2 - An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations

AU - Böhmer, Wendelin

AU - Springenberg, Jost Tobias

AU - Boedecker, Joschka

AU - Riedmiller, Martin

AU - Obermayer, Klaus

PY - 2015

Y1 - 2015

U2 - 10.1007/s13218-015-0356-1

DO - 10.1007/s13218-015-0356-1

M3 - Article

SN - 0933-1875

VL - 29

SP - 353

EP - 362

JO - KI - Künstliche Intelligenz

JF - KI - Künstliche Intelligenz

IS - 4

ER -