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PyTorch 1.x Reinforcement Learning Cookbook

You're reading from   PyTorch 1.x Reinforcement Learning Cookbook Over 60 recipes to design, develop, and deploy self-learning AI models using Python

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781838551964
Length 340 pages
Edition 1st Edition
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Author (1):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started with Reinforcement Learning and PyTorch 2. Markov Decision Processes and Dynamic Programming FREE CHAPTER 3. Monte Carlo Methods for Making Numerical Estimations 4. Temporal Difference and Q-Learning 5. Solving Multi-armed Bandit Problems 6. Scaling Up Learning with Function Approximation 7. Deep Q-Networks in Action 8. Implementing Policy Gradients and Policy Optimization 9. Capstone Project – Playing Flappy Bird with DQN 10. Other Books You May Enjoy

Technical requirements

You will need the following programs installed on your system to successfully execute the recipes in this chapter:

  • Python 3.6, 3.7, or above
  • Anaconda
  • PyTorch 1.0 or above
  • OpenAI Gym
You have been reading a chapter from
PyTorch 1.x Reinforcement Learning Cookbook
Published in: Oct 2019
Publisher: Packt
ISBN-13: 9781838551964
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