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Reinforcement Learning with TensorFlow

You're reading from Reinforcement Learning with TensorFlow

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788835725

Pages 334 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Sayon Dutta

Table of Contents (21) Chapters

Title Page

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Contributors

Preface

1. Deep Learning – Architectures and Frameworks

2. Training Reinforcement Learning Agents Using OpenAI Gym

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

1. Further topics in Reinforcement Learning

2. Other Books You May Enjoy

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Index

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, structures, and their varied high dimensional features. Thus, the goal would be to take the optimal actions to survive in the gaming...

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Authors (1)

Sayon Dutta

Sayon Dutta is an Artificial Intelligence researcher and developer. A graduate from IIT Kharagpur, he owns the software copyright for Mobile Irrigation Scheduler. At present, he is an AI engineer at Wissen Technology. He co-founded an AI startup Marax AI Inc., focused on AI-powered customer churn prediction. With over 2.5 years of experience in AI, he invests most of his time implementing AI research papers for industrial use cases, and weightlifting.

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