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Hands-On Reinforcement Learning with Python

You're reading from Hands-On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788836524

Length 318 pages

Edition 1st Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Deep Reinforcement Learning

Author (1):

Sudharsan Ravichandiran

View More author details

Table of Contents (16) Chapters

Preface

1. Introduction to Reinforcement Learning

2. Getting Started with OpenAI and TensorFlow FREE CHAPTER

3. The Markov Decision Process and Dynamic Programming

4. Gaming with Monte Carlo Methods

5. Temporal Difference Learning

6. Multi-Armed Bandit Problem

7. Deep Learning Fundamentals

8. Atari Games with Deep Q Network

9. Playing Doom with a Deep Recurrent Q Network

10. The Asynchronous Advantage Actor Critic Network

11. Policy Gradients and Optimization

12. Capstone Project – Car Racing Using DQN

13. Recent Advancements and Next Steps

14. Assessments

15. Other Books You May Enjoy

Leave a review - let other readers know what you think

OpenAI Universe

OpenAI Universe provides a wide range of realistic gaming environments. It is an extension to OpenAI Gym. It provides the ability to train and evaluate agents on a wide range of simple to real-time complex environments. It has unlimited access to many gaming environments.

Building a video game bot

Let's learn how to build a video game bot which plays a car racing game. Our objective is that the car has to move forward without getting stuck on any obstacles or hitting other cars.

First, we import the necessary libraries:

import gym
import universe # register universe environment
import random

Then we simulate our car racing environment using the make function:

env = gym.make('flashgames.NeonRace-v0...

You have been reading a chapter from

Hands-On Reinforcement Learning with Python

Published in: Jun 2018

Publisher: Packt

ISBN-13: 9781788836524

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Authors (1)

Sudharsan Ravichandiran

Sudharsan Ravichandiran

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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