Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

Daniel Tanneberg; Jan Peters; Elmar Rueckert

doi:10.1016/j.neunet.2018.10.005

Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

Daniel Tanneberg, Jan Peters, Elmar Rueckert

Chair of Cyber Physical Systems (190)

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

4 Citations (Scopus)

Original language	English
Pages (from-to)	67-80
Number of pages	14
Journal	Neural networks
Volume	109
DOIs	https://doi.org/10.1016/j.neunet.2018.10.005
Publication status	Published - Jan 2019

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

Autonomous robots
Experience replay
Intrinsic motivation
Neural sampling
Online learning
Spiking recurrent networks

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10.1016/j.neunet.2018.10.005

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title = "Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks",

keywords = "Autonomous robots, Experience replay, Intrinsic motivation, Neural sampling, Online learning, Spiking recurrent networks",

author = "Daniel Tanneberg and Jan Peters and Elmar Rueckert",

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year = "2019",

month = jan,

doi = "10.1016/j.neunet.2018.10.005",

language = "English",

volume = "109",

pages = "67--80",

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AU - Tanneberg, Daniel

AU - Peters, Jan

AU - Rueckert, Elmar

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KW - Autonomous robots

KW - Experience replay

KW - Intrinsic motivation

KW - Neural sampling

KW - Online learning

KW - Spiking recurrent networks

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DO - 10.1016/j.neunet.2018.10.005

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SN - 0893-6080

VL - 109

SP - 67

EP - 80

JO - Neural networks

JF - Neural networks

ER -

Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

Bibliographical note

Keywords

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