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Hands-On Reinforcement Learning with Python

You're reading from  Hands-On Reinforcement Learning with Python

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788836524
Pages 318 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sudharsan Ravichandiran Sudharsan Ravichandiran
Profile icon Sudharsan Ravichandiran
LinkedIn
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
See other products by Sudharsan Ravichandiran

Table of Contents (16) Chapters

Preface Introduction to Reinforcement Learning Getting Started with OpenAI and TensorFlow The Markov Decision Process and Dynamic Programming Gaming with Monte Carlo Methods Temporal Difference Learning Multi-Armed Bandit Problem Deep Learning Fundamentals Atari Games with Deep Q Network Playing Doom with a Deep Recurrent Q Network The Asynchronous Advantage Actor Critic Network Policy Gradients and Optimization Capstone Project – Car Racing Using DQN Recent Advancements and Next Steps Assessments Other Books You May Enjoy

To get the most out of this book

You need the following software for this book:

  • Anaconda
  • Python
  • Any web browser
  • Docker

Download the example code files

You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packtpub.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Reinforcement-Learning-with-Python. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system."

A block of code is set as follows:

policy_iteration():
    Initialize random policy
    for i in no_of_iterations: 
        Q_value = value_function(random_policy)
        new_policy = Maximum state action pair from Q value

Any command-line input or output is written as follows:

bash Anaconda3-5.0.1-Linux-x86_64.sh

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this.

Warnings or important notes appear like this.
Tips and tricks appear like this.
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Authors (1)

Profile icon Sudharsan Ravichandiran
LinkedIn
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
See other products by Sudharsan Ravichandiran

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