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Hands-On Reinforcement Learning with Python

You're reading from Hands-On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788836524

Length 318 pages

Edition 1st Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Deep Reinforcement Learning

Author (1):

Sudharsan Ravichandiran

View More author details

Table of Contents (16) Chapters

Preface

1. Introduction to Reinforcement Learning

2. Getting Started with OpenAI and TensorFlow FREE CHAPTER

3. The Markov Decision Process and Dynamic Programming

4. Gaming with Monte Carlo Methods

5. Temporal Difference Learning

6. Multi-Armed Bandit Problem

7. Deep Learning Fundamentals

8. Atari Games with Deep Q Network

9. Playing Doom with a Deep Recurrent Q Network

10. The Asynchronous Advantage Actor Critic Network

11. Policy Gradients and Optimization

12. Capstone Project – Car Racing Using DQN

13. Recent Advancements and Next Steps

14. Assessments

15. Other Books You May Enjoy

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Long Short-Term Memory RNN

RNNs are pretty cool, right? But we have seen a problem in training the RNNs called the vanishing gradient problem. Let's explore that a bit. The sky is __. An RNN can easily predict the last word as blue based on the information it has seen. But an RNN cannot cover long-term dependencies. What does that mean? Let's say Archie lived in China for 20 years. He loves listening to good music. He is a very big comic fan. He is fluent in _. Now, you would predict the blank as Chinese. How did you predict that? Because you understood that Archie lived for 20 years in China, you thought he might be fluent in Chinese. But an RNN cannot retain all of this information in memory to say that Archie is fluent in Chinese. Due to the vanishing gradient problem, it cannot recollect/remember the information for a long time in memory. How do we solve that?

Here...

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Authors (1)

Sudharsan Ravichandiran

Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

See other products by Sudharsan Ravichandiran

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