Kernel dynamic policy programming: applicable reinforcement learning to robot systems with high dimensional states

DOI10.1016/J.NEUNET.2017.06.007zbMath1429.68212DBLPjournals/nn/CuiMS17OpenAlexW2730929966WikidataQ47756366 ScholiaQ47756366MaRDI QIDQ2292214

Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto

Publication date: 3 February 2020

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2017.06.007

zbMATH Keywords

kernel methodsreinforcement learningrobot learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Artificial intelligence for robotics (68T40)

Cites Work

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• \({\mathcal Q}\)-learning
• Least squares policy evaluation algorithms with linear function approximation
• Multiple Model-Based Reinforcement Learning
• 10.1162/1532443041827907

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