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Deep Reinforcement Learning with Python

You're reading from   Deep Reinforcement Learning with Python Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781839210686
Length 760 pages
Edition 2nd Edition
Languages
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Toc

Table of Contents (22) Chapters Close

Preface 1. Fundamentals of Reinforcement Learning 2. A Guide to the Gym Toolkit FREE CHAPTER 3. The Bellman Equation and Dynamic Programming 4. Monte Carlo Methods 5. Understanding Temporal Difference Learning 6. Case Study – The MAB Problem 7. Deep Learning Foundations 8. A Primer on TensorFlow 9. Deep Q Network and Its Variants 10. Policy Gradient Method 11. Actor-Critic Methods – A2C and A3C 12. Learning DDPG, TD3, and SAC 13. TRPO, PPO, and ACKTR Methods 14. Distributional Reinforcement Learning 15. Imitation Learning and Inverse RL 16. Deep Reinforcement Learning with Stable Baselines 17. Reinforcement Learning Frontiers 18. Other Books You May Enjoy
19. Index
Appendix 1 – Reinforcement Learning Algorithms 1. Appendix 2 – Assessments

LSTM to the rescue

While backpropagating an RNN, we learned about a problem called vanishing gradients. Due to the vanishing gradient problem, we cannot train the network properly, and this causes the RNN to not retain long sequences in the memory. To understand what we mean by this, let's consider a small sentence:

The sky is __.

An RNN can easily predict the blank as blue based on the information it has seen, but it cannot cover the long-term dependencies. What does that mean? Let's consider the following sentence to understand the problem better:

Archie lived in China for 13 years. He loves listening to good music. He is a fan of comics. He is fluent in ____.

Now, if we were asked to predict the missing word in the preceding sentence, we would predict it as Chinese, but how did we predict that? We simply remembered the previous sentences and understood that Archie lived for 13 years in China. This led us to the conclusion that...

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