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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Deep Reinforcement Learning: An Overview

verfasst von : Seyed Sajad Mousavi, Michael Schukat, Enda Howley

Erschienen in: Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016

Verlag: Springer International Publishing

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Abstract

In recent years, a specific machine learning method called deep learning has gained huge attraction, as it has obtained astonishing results in broad applications such as pattern recognition, speech recognition, computer vision, and natural language processing. Recent research has also been shown that deep learning techniques can be combined with reinforcement learning methods to learn useful representations for the problems with high dimensional raw data input. This article reviews the recent advances in deep reinforcement learning with focus on the most used deep architectures such as autoencoders, convolutional neural networks and recurrent neural networks which have successfully been come together with the reinforcement learning framework.

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Metadaten
Titel
Deep Reinforcement Learning: An Overview
verfasst von
Seyed Sajad Mousavi
Michael Schukat
Enda Howley
Copyright-Jahr
2018
Buch
Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016

Print ISBN: 978-3-319-56990-1

Electronic ISBN: 978-3-319-56991-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-56991-8_32