Deep Reinforcement Learning: An Overview

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 recognizeton, 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 paper reviews the recent advances in deep reinforcement learning with a focus on the most used deep architectures such as auto encoders, convolutional neural networks and recurrent neural networks which have successfully been come together with the reinforcement learning framework.