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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

Packt Upsell

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

Summary

In this chapter, we discussed real strategy games and why researchers from the AI community are trying to solve them. We also covered the complexity and properties of real strategy games and the different traditional AI approaches, such as case-based reasoning and online case-based planning to solve them and their drawbacks. We discussed the reason behind reinforcement learning being the perfect candidate for the problem and how it is successful in fulfilling the complexity and issues related to real-time strategy games where earlier traditional AI approaches failed. We also learnt about deep autoencoders and how they can be used to reduce the dimensionality of the input data and obtain a better representation of the input.

In the next chapter, we will cover the most famous topic that brought deep reinforcement learning into the limelight and made it the flag bearer of AI algorithms, that is, Alpha Go.

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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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