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TensorFlow 2 Reinforcement Learning Cookbook

You're reading from   TensorFlow 2 Reinforcement Learning Cookbook Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781838982546
Length 472 pages
Edition 1st Edition
Languages
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Author (1):
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Palanisamy Palanisamy
Author Profile Icon Palanisamy
Palanisamy
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Toc

Table of Contents (11) Chapters Close

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 FREE CHAPTER 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

Building a visual auto-login bot

Imagine that you have an Agent or a bot that watches what you are doing and automatically logs you into websites whenever you click on a login screen. While browser plugins exist that can automatically log you in, they do so using hardcoded scripts that only work on the pre-programmed website's login URLs. But what if you had an Agent that only relied on the rendered web page – just like you do to perform a task – and worked even when the URL changes and when you are on a new website with no prior saved data? How cool would that be?! This recipe will help you develop a script that will train an Agent to log in on a web page! You will learn how to randomize, customize, and increase the generality of the Agent to get it to work on any login screen.

An example of randomizing and customizing the usernames and passwords for a task can be seen in the following image:

Figure 6.8 – Sample observations from...

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