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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

Reinforcement Learning

Author (1):

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

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Sections

In this book, you will find several headings that appear frequently (Getting ready, How to do it..., How it works..., There's more..., and See also).

To give clear instructions on how to complete a recipe, use these sections as follows:

Getting ready

This section tells you what to expect in the recipe and describes how to set up any software or any preliminary settings required for the recipe.

How to do it...

This section contains the steps required to follow the recipe.

How it works...

This section usually consists of a detailed explanation of what happened in the previous section.

There's more...

This section consists of additional information about the recipe in order to make you more knowledgeable about the recipe.

See also

This section provides helpful links to other useful information for the recipe.

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Authors (1)

Yuxi (Hayden) Liu

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.

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