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General Value Function Networks.

arXiv: Learning, (2019)

Cited by: 6|Views13
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Abstract

In this paper we show that restricting the representation-layer of a Recurrent Neural Network (RNN) improves accuracy and reduces the depth of recursive training procedures in partially observable domains. Artificial Neural Networks have been shown to learn useful state representations for high-dimensional visual and continuous control do...More

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Author
Matthew Schlegel
Matthew Schlegel
Andrew Patterson
Andrew Patterson
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