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The Reinforcement Learning Workshop

You're reading from   The Reinforcement Learning Workshop Learn how to apply cutting-edge reinforcement learning algorithms to a wide range of control problems

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800200456
Length 822 pages
Edition 1st Edition
Languages
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Authors (9):
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Dr. Alexandra Galina Petre Dr. Alexandra Galina Petre
Author Profile Icon Dr. Alexandra Galina Petre
Dr. Alexandra Galina Petre
Anand N.S. Anand N.S.
Author Profile Icon Anand N.S.
Anand N.S.
Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Mayur Kulkarni Mayur Kulkarni
Author Profile Icon Mayur Kulkarni
Mayur Kulkarni
Aritra Sen Aritra Sen
Author Profile Icon Aritra Sen
Aritra Sen
Alessandro Palmas Alessandro Palmas
Author Profile Icon Alessandro Palmas
Alessandro Palmas
Emanuele Ghelfi Emanuele Ghelfi
Author Profile Icon Emanuele Ghelfi
Emanuele Ghelfi
Saikat Basak Saikat Basak
Author Profile Icon Saikat Basak
Saikat Basak
+5 more Show less
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Table of Contents (14) Chapters Close

Preface
1. Introduction to Reinforcement Learning 2. Markov Decision Processes and Bellman Equations FREE CHAPTER 3. Deep Learning in Practice with TensorFlow 2 4. Getting Started with OpenAI and TensorFlow for Reinforcement Learning 5. Dynamic Programming 6. Monte Carlo Methods 7. Temporal Difference Learning 8. The Multi-Armed Bandit Problem 9. What Is Deep Q-Learning? 10. Playing an Atari Game with Deep Recurrent Q-Networks 11. Policy-Based Methods for Reinforcement Learning 12. Evolutionary Strategies for RL Appendix

Understanding the Breakout Environment

We will be training different deep reinforcement learning agents to play the game Breakout in this chapter. Before diving in, let's learn some more about the game.

Breakout is an arcade game designed and released in 1976 by Atari. Steve Wozniak, co-founder of Apple, was part of the design and development team. The game was extremely popular at that time and multiple versions were developed over the years.

The goal of the game is to break all the bricks located at the top of the screen with a ball (since the game was developed in 1974 with low screen definition, the ball is represented by pixels and so its shape can be seen as a rectangle in the following screenshot) without dropping it. The player can move a paddle horizontally at the bottom of the screen to hit the ball before it drops and bounce it back toward the bricks. Also, the ball will bounce back after hitting the side walls or the ceiling. The game ends when either the ball...

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