preprintarXiv (Cornell University)Aug 19, 2017GREEN OA

A Brief Survey of Deep Reinforcement Learning

Indexed inarxivdatacite

Abstract

Deep reinforcement learning is poised to revolutionise the field of AI and represents a step towards building autonomous systems with a higher level understanding of the visual world. Currently, deep learning is enabling reinforcement learning to scale to problems that were previously intractable, such as learning to play video games directly from pixels. Deep reinforcement learning algorithms are also applied to robotics, allowing control policies for robots to be learned directly from camera inputs in the real world. In this survey, we begin with an introduction to the general field of reinforcement learning, then progress to the main streams of value-based and policy-based methods. Our survey will cover…

Citation impact

752
total citations
FWCI
Percentile
References
121
Citations per year

Authors

4

Topics & keywords

Keywords
  • Reinforcement learning
  • Artificial intelligence
  • Deep learning
  • Computer science
  • Field (mathematics)
  • Robotics
  • Artificial neural network
  • Machine learning
UN Sustainable Development Goals
  • Partnerships for the goals
No related works found for this paper.