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Hands-On Deep Learning for Games

You're reading from   Hands-On Deep Learning for Games Leverage the power of neural networks and reinforcement learning to build intelligent games

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781788994071
Length 392 pages
Edition 1st Edition
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Author (1):
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Micheal Lanham Micheal Lanham
Author Profile Icon Micheal Lanham
Micheal Lanham
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Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics FREE CHAPTER
2. Deep Learning for Games 3. Convolutional and Recurrent Networks 4. GAN for Games 5. Building a Deep Learning Gaming Chatbot 6. Section 2: Deep Reinforcement Learning
7. Introducing DRL 8. Unity ML-Agents 9. Agent and the Environment 10. Understanding PPO 11. Rewards and Reinforcement Learning 12. Imitation and Transfer Learning 13. Building Multi-Agent Environments 14. Section 3: Building Games
15. Debugging/Testing a Game with DRL 16. Obstacle Tower Challenge and Beyond 17. Other Books You May Enjoy

RL with the OpenAI Gym

RL has become so popular that there is now a race to just build tools that help build RL algorithms. The two major competitors in this area right now are OpenAI Gym and Unity. Unity has quickly become the RL racing machine we will explore extensively later. For now, we will put our training wheels on and run OpenAI Gym to explore the fundamentals of RL further.

We need to install the OpenAI Gym toolkit before we can continue, and installation may vary greatly depending on your operating system. As such, we will focus on the Windows installation instructions here, as it is likely other OS users will have less difficulty. Follow the next steps to install OpenAI Gym on Windows:

  1. Install a C++ compiler; if you have Visual Studio 2017 installed, you may already have a recommended one. You can find other supported compilers here: https://wiki.python.org/moin/WindowsCompilers...
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