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Hands-On Q-Learning with Python

You're reading from   Hands-On Q-Learning with Python Practical Q-learning with OpenAI Gym, Keras, and TensorFlow

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789345803
Length 212 pages
Edition 1st Edition
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Author (1):
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Nazia Habib Nazia Habib
Author Profile Icon Nazia Habib
Nazia Habib
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Table of Contents (14) Chapters Close

Preface 1. Section 1: Q-Learning: A Roadmap FREE CHAPTER
2. Brushing Up on Reinforcement Learning Concepts 3. Getting Started with the Q-Learning Algorithm 4. Setting Up Your First Environment with OpenAI Gym 5. Teaching a Smartcab to Drive Using Q-Learning 6. Section 2: Building and Optimizing Q-Learning Agents
7. Building Q-Networks with TensorFlow 8. Digging Deeper into Deep Q-Networks with Keras and TensorFlow 9. Section 3: Advanced Q-Learning Challenges with Keras, TensorFlow, and OpenAI Gym
10. Decoupling Exploration and Exploitation in Multi-Armed Bandits 11. Further Q-Learning Research and Future Projects 12. Assessments 13. Other Books You May Enjoy

Section 3: Advanced Q-Learning Challenges with Keras, TensorFlow, and OpenAI Gym

The reader will be introduced to more advanced Q-learning problems and will get suggestions on how to take an RL approach to real-world problems. They will become familiar with research in Q-learning and the current problems practitioners are working on solving. They will leave this section with a sense of what is coming up next in RL and how they can apply their skills to those problems moving forward.

The following chapters are included in this section:

  • Chapter 7, Decoupling Exploration and Exploitation in Multi-Armed Bandits
  • Chapter 8, Further Q-Learning Research and Future Projects
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