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PyTorch 1.x Reinforcement Learning Cookbook

You're reading from  PyTorch 1.x Reinforcement Learning Cookbook

Product type Book
Published in Oct 2019
Publisher Packt
ISBN-13 9781838551964
Pages 340 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Profile icon Yuxi (Hayden) Liu
LinkedIn
Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
See other products by Yuxi (Hayden) Liu

Table of Contents (11) Chapters

Preface Getting Started with Reinforcement Learning and PyTorch Markov Decision Processes and Dynamic Programming Monte Carlo Methods for Making Numerical Estimations Temporal Difference and Q-Learning Solving Multi-armed Bandit Problems Scaling Up Learning with Function Approximation Deep Q-Networks in Action Implementing Policy Gradients and Policy Optimization Capstone Project – Playing Flappy Bird with DQN Other Books You May Enjoy

Setting up the continuous Mountain Car environment

So far, the environments we have worked on have discrete action values, such as 0 or 1, representing up or down, left or right. In this recipe, we will experience a Mountain Car environment with continuous actions.

Continuous Mountain Car (https://github.com/openai/gym/wiki/MountainCarContinuous-v0) is a Mountain Car environment with continuous actions whose value is from -1 to 1. As shown in the following screenshot, its goal is to get the car to the top of the hill on the right-hand side:

In a one-dimensional track, the car is positioned between -1.2 (leftmost) and 0.6 (rightmost), and the goal (yellow flag) is located at 0.5. The engine of the car is not strong enough to drive it to the top in a single pass, so it has to drive back and forth to build up momentum. Hence, the action is a float that represents the force of pushing...

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Authors (1)

Profile icon Yuxi (Hayden) Liu
LinkedIn
Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
Read more
See other products by Yuxi (Hayden) Liu

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