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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

Further improvements

There are further improvements that can be made to the previous framework, and also better approaches to creating end to end financial portfolio managing agents using deep reinforcement learning. They are as follows:

Current framework assumptions, which are zero slippage and zero market impact. Thus, considering market impact and slippage will provide real-world trading samples, which will improve the training dataset.
Use of an actor-critic type of framework will help more in long-term market reactions.
Preferring LSTMs and GRUs over basic RNNs overcomes the issue of the vanishing gradient problem.

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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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