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TensorFlow 2 Reinforcement Learning Cookbook

You're reading from TensorFlow 2 Reinforcement Learning Cookbook

Product type Book

Published in Jan 2021

Publisher Packt

ISBN-13 9781838982546

Pages 472 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Palanisamy P

Table of Contents (11) Chapters

Preface

1. Chapter 1: Developing Building Blocks for Deep Reinforcement Learning Using Tensorflow 2.x

2. Chapter 2: Implementing Value-Based, Policy-Based, and Actor-Critic Deep RL Algorithms

3. Chapter 3: Implementing Advanced RL Algorithms

4. Chapter 4: Reinforcement Learning in the Real World – Building Cryptocurrency Trading Agents

5. Chapter 5: Reinforcement Learning in the Real World – Building Stock/Share Trading Agents

6. Chapter 6: Reinforcement Learning in the Real World – Building Intelligent Agents to Complete Your To-Dos

7. Chapter 7: Deploying Deep RL Agents to the Cloud

8. Chapter 8: Distributed Training for Accelerated Development of Deep RL Agents

9. Chapter 9: Deploying Deep RL Agents on Multiple Platforms

10. Other Books You May Enjoy

Leave a review - let other readers know what you think

Training an RL Agent to manage your emails

Email has become an integral part of many people's lives. The number of emails that an average working professional goes through in a workday is growing daily. While a lot of email filters exist for spam control, how nice would it be to have an intelligent Agent that can perform a series of email management tasks that just provide a task description (through text or speech via speech-to-text) and are not limited by any APIs that have rate limits? In this recipe, you will develop a deep RL Agent and train it on email management tasks! A set of sample tasks can be seen in the following image:

Figure 6.15 – A sample set of observations from the randomized MiniWoBEmailInboxImportantVisualEnv environment

Let's get into the details!

Getting ready

To complete this recipe, make sure you have the latest version. First, you will need to activate the tf2rl-cookbook Python/conda virtual environment. Make...

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Authors (1)

Palanisamy P

Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.

See other products by Palanisamy P

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