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Reinforcement Learning with TensorFlow

You're reading from   Reinforcement Learning with TensorFlow A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788835725
Length 334 pages
Edition 1st Edition
Languages
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Author (1):
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Sayon Dutta Sayon Dutta
Author Profile Icon Sayon Dutta
Sayon Dutta
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Toc

Table of Contents (17) Chapters Close

Preface 1. Deep Learning – Architectures and Frameworks 2. Training Reinforcement Learning Agents Using OpenAI Gym FREE CHAPTER 3. Markov Decision Process 4. Policy Gradients 5. Q-Learning and Deep Q-Networks 6. Asynchronous Methods 7. Robo Everything – Real Strategy Gaming 8. AlphaGo – Reinforcement Learning at Its Best 9. Reinforcement Learning in Autonomous Driving 10. Financial Portfolio Management 11. Reinforcement Learning in Robotics 12. Deep Reinforcement Learning in Ad Tech 13. Reinforcement Learning in Image Processing 14. Deep Reinforcement Learning in NLP 15. Further topics in Reinforcement Learning 16. Other Books You May Enjoy

Real-time strategy games

The term real-time strategy (RTS) was first used by Brett Sperry as a tagline to market their game Dune II. Real-time strategy games involve the player using real-time tactics to increase assets, and save them, and utilizing them to destroy the assets of the opponent. It is associated with the many complex tactical decisions that need to be taken in a very short period of time. 

This is different from turn-based strategy games, where each opponent has time to analyze and take action while other opponents couldn't perform any actions. In real-time strategy games, the action and reaction both take place in real time, since the other entities in the environment, that is, opponents, are also active and will be performing actions simultaneously. In a real strategy game environment, there are varied forms of entities, which include players...

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