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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
2. Deep Learning for Games FREE CHAPTER 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

Running the chatbot in Unity

Unity is quickly becoming the standard game engine for learning to develop games, virtual reality, and augmented reality applications. Now it is quickly becoming the standard platform for developing AI and ML applications as well, partly due to the excellent reinforcement learning platform the team at Unity has built. This Unity ML platform is a key component in our desire to use the tool, since it currently is at the cutting edge of advanced AI for games.

The AI team at Unity, led by Dr. Danny Lange and their senior developer Dr. Arthur Juliani, have made numerous suggestions and contributions to ideas for content in this book, both directly and indirectly. This, of course, has had a huge impact on using Unity for major portions of this book.

Installing Unity is quite straightforward, but we want to make sure we get the installation just right the...

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