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Reinforcement Learning with TensorFlow

You're reading from   Reinforcement Learning with TensorFlow A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788835725
Length 334 pages
Edition 1st Edition
Languages
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Author (1):
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Sayon Dutta Sayon Dutta
Author Profile Icon Sayon Dutta
Sayon Dutta
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Toc

Table of Contents (17) Chapters Close

Preface 1. Deep Learning – Architectures and Frameworks FREE CHAPTER 2. Training Reinforcement Learning Agents Using OpenAI Gym 3. Markov Decision Process 4. Policy Gradients 5. Q-Learning and Deep Q-Networks 6. Asynchronous Methods 7. Robo Everything – Real Strategy Gaming 8. AlphaGo – Reinforcement Learning at Its Best 9. Reinforcement Learning in Autonomous Driving 10. Financial Portfolio Management 11. Reinforcement Learning in Robotics 12. Deep Reinforcement Learning in Ad Tech 13. Reinforcement Learning in Image Processing 14. Deep Reinforcement Learning in NLP 15. Further topics in Reinforcement Learning 16. Other Books You May Enjoy

Hierarchical object detection with deep reinforcement learning

In this section, we will try to understand how deep reinforcement learning can be applied for hierarchical object detection as per the framework suggested in Hierarchical Object Detection with Deep Reinforcement Learning by Bellver et. al. (2016)(https://arxiv.org/pdf/1611.03718.pdf). This experiment showcases a method to perform hierarchical object detection in images using deep reinforcement learning with the main focus on important parts of the image carrying richer information. The objective here was to train a deep reinforcement learning agent to which an image window is given and the image gets further segregated into five smaller windows and the agent is successfully able to focus its attention on one of the smaller windows.

Now let's consider how we humans look at an image. We always extract information...

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