0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Deep Reinforcement Learning with Python

You're reading from Deep Reinforcement Learning with Python Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow

Product type Paperback

Published in Sep 2020

Publisher Packt

ISBN-13 9781839210686

Length 760 pages

Edition 2nd Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Deep Reinforcement Learning

Author (1):

Sudharsan Ravichandiran

View More author details

Table of Contents (22) Chapters

Preface

1. Fundamentals of Reinforcement Learning

2. A Guide to the Gym Toolkit FREE CHAPTER

3. The Bellman Equation and Dynamic Programming

4. Monte Carlo Methods

5. Understanding Temporal Difference Learning

6. Case Study – The MAB Problem

7. Deep Learning Foundations

8. A Primer on TensorFlow

9. Deep Q Network and Its Variants

10. Policy Gradient Method

11. Actor-Critic Methods – A2C and A3C

12. Learning DDPG, TD3, and SAC

13. TRPO, PPO, and ACKTR Methods

14. Distributional Reinforcement Learning

15. Imitation Learning and Inverse RL

16. Deep Reinforcement Learning with Stable Baselines

17. Reinforcement Learning Frontiers

18. Other Books You May Enjoy

19. Index

Appendix 1 – Reinforcement Learning Algorithms

1. Appendix 2 – Assessments

Further reading

To learn more, check the following resource:

Check out the Stable Baselines documentation, available at https://stable-baselines.readthedocs.io/en/master/index.html

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €18.99/month. Cancel anytime

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

Other recommended products

Related to this chapter

Hands-On Reinforcement Learning with Python

Hands-On Reinforcement Learning with Python

Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.

Jun 2018 10h 36m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Hands-On Meta Learning with Python

Hands-On Meta Learning with Python

This hands-on guide for meta learning starts with exploring the principles, algorithms, and implementations of Meta learning with Tensorflow, Keras, and Python. Once it sets the foundation of "learning to learn", the book will help you implement your meta learning algorithms from scratch.

Dec 2018 7h 32m

PyTorch 1.x Reinforcement Learning Cookbook

PyTorch 1.x Reinforcement Learning Cookbook

This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Oct 2019 11h 20m

TensorFlow Reinforcement Learning Quick Start Guide

TensorFlow Reinforcement Learning Quick Start Guide

This book is an essential guide for anyone interested in Reinforcement Learning. The book provides an actionable reference for Reinforcement Learning algorithms and their applications using TensorFlow and Python. It will help readers leverage the power of algorithms such as Deep Q-Network (DQN), Deep Deterministic Policy Gradients (DDPG), and Proximal Policy Optimization (PPO) to solve challenging control and decision-making problems.

TensorFlow 2 Reinforcement Learning Cookbook

TensorFlow 2 Reinforcement Learning Cookbook

This cookbook will help you to gain a solid understanding of deep reinforcement learning (RL) algorithms with the help of concise, easy-to-follow implementations from scratch. You'll learn how to implement these algorithms with minimal code and develop AI applications to solve real-world and business problems using RL.

Jan 2021 15h 44m

Reinforcement Learning Algorithms with Python

Reinforcement Learning Algorithms with Python

With this book, you will understand the core concepts and techniques of reinforcement learning. You will take a look into each RL algorithm and will develop your own self-learning algorithms and models. You will optimize the algorithms for better precision, use high-speed actions and lower the risk of anomalies in your applications.

Oct 2019 12h 12m

Reinforcement Learning with TensorFlow

Reinforcement Learning with TensorFlow

Reinforcement learning allows you to develop intelligent, self-learning systems. This book shows you how to put the concepts of Reinforcement Learning to train efficient models.You will use popular reinforcement learning algorithms to implement use-cases in image processing and NLP, by combining the power of TensorFlow and OpenAI Gym.

Apr 2018 11h 8m

Hands-On Intelligent Agents with OpenAI Gym

Hands-On Intelligent Agents with OpenAI Gym

Walks through the hands-on process of building intelligent agents from the basics and all the way up to solving complex problems including playing Atari games and driving a car autonomously in the CARLA simulator. Discusses various learning environments and how to transform real-world problems into learning environments and solve using the agents.

Jul 2018 8h 28m

Practical Reinforcement Learning

Practical Reinforcement Learning

Reinforcement learning (RL) is becoming a popular tool for constructing autonomous systems that improve themselves with experience. We will break the RL framework into its core building blocks, and provide you with details of each element. This book is divided into three parts. The first part defines Reinforcement Learning and describes the basics and the Python and Java frameworks, which we are going to use later in the book. The second part discusses learning techniques with basic algorithms such as Temporal Difference, Monte Carlo, and Policy Gradient—all with practical examples. Lastly, in the third part we apply Reinforcement Learning with the most recent and widely used algorithms, via practical applications.

Oct 2017 11h 12m

Python Reinforcement Learning Projects

Python Reinforcement Learning Projects

Python Reinforcement Learning Projects brings various aspects and methodologies of RL using 8 real-world projects that explore RL and will have hands-on experience with real data and artificial intelligence problems. You will learn to build self-learning models using sophisticated techniques like Q-learning, Markov models and Monte-Carlo process.

Sep 2018 9h 52m

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python

Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.

Personalised recommendations for you

Based on your interests and search pattern

Pragmatic Microservices with C# and Azure

Pragmatic Microservices with C# and Azure

This book empowers you with in-depth knowledge of microservices architecture using .NET and Azure. Through hands-on tutorials, you'll be able to build, deploy, and manage scalable applications, gaining crucial skills for modern software development.

May 2024 16h 56m

Mastering Python Design Patterns

Mastering Python Design Patterns

Unlock the power of design patterns to build maintainable and scalable software and applications using Python. Authored by Python veterans, this book is your guide to mastering design patterns in Python.

May 2024 9h 52m

System Programming Essentials with Go

System Programming Essentials with Go

From file operations to process management and network programming, this hands-on guide equips software engineers with the skills to build efficient, reliable applications and optimize their performance.

Jun 2024 13h 36m

Modern Python Cookbook

Modern Python Cookbook

The new edition of Modern Python Cookbook provides over 130 recipes for solving real-world problems with Python. Updated for Python 3.12 with new recipes and chapters. This practical guide will enhance your skills and teach you advanced techniques.

Jul 2024 27h 16m

The Ultimate Zoom Cookbook

The Ultimate Zoom Cookbook

This cookbook is an in-depth guide to using Zoom effectively. You'll be able to follow each recipe easily to harness the power of the communication and collaboration tools in Zoom.

May 2024 11h 20m

Enterprise Architecture with .NET

Enterprise Architecture with .NET

This book will help you create applications that integrate correctly into complex and ever-changing information systems. You'll execute this by using industry standards that reduce the app's technical debt and elevate software development practices.

May 2024 25h 44m

Salesforce B2C Solution Architect's Handbook

Salesforce B2C Solution Architect's Handbook

Discover how Salesforce Customer 360 unifies Marketing Cloud, B2C Commerce, Data Cloud, and Service Cloud into one solution, and learn the capabilities, integration options, limitations, and workflows to create value for your organization.

May 2024 15h 28m

Systems Programming with C# and .NET

Systems Programming with C# and .NET

Unlock the full potential of C# and .NET Core in systems programming to secure, deploy, and maintain robust applications. With this book, you'll focus on low-level APIs, memory management, and performance optimization.

Jul 2024 15h 48m

Technical Program Manager's Handbook

Technical Program Manager's Handbook

Unlock the full potential of your career as a TPM with this comprehensive guide, featuring new chapters on AI and more. Learn advanced techniques and gain insights from industry leaders. Elevate your skills and thrive in the Big Five tech companies.

Sep 2024 12h 16m

Microsoft Power Pages in Action

Microsoft Power Pages in Action

Packed with real-world examples, low-code coding techniques, and insights into crafting responsive pages, automating apps, and enhancing virtual agents, Microsoft Power Pages in Action is a valuable resource for building feature-rich web apps.

Jun 2024 11h 40m