Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Learning Hub

Conferences

Free Learning

Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges

Lonza

€29.99

3 (3 Ratings)

Paperback Oct 2019 366 pages 1st Edition

Lonza

€29.99

3 (3 Ratings)

Paperback Oct 2019 366 pages 1st Edition

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

View table of contents

Preview Book

Download Code

Key benefits

Learn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasks
Understand and develop model-free and model-based algorithms for building self-learning agents
Work with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution strategies

Description

Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will help you master RL algorithms and understand their implementation as you build self-learning agents. Starting with an introduction to the tools, libraries, and setup needed to work in the RL environment, this book covers the building blocks of RL and delves into value-based methods, such as the application of Q-learning and SARSA algorithms. You'll learn how to use a combination of Q-learning and neural networks to solve complex problems. Furthermore, you'll study the policy gradient methods, TRPO, and PPO, to improve performance and stability, before moving on to the DDPG and TD3 deterministic algorithms. This book also covers how imitation learning techniques work and how Dagger can teach an agent to drive. You'll discover evolutionary strategies and black-box optimization techniques, and see how they can improve RL algorithms. Finally, you'll get to grips with exploration approaches, such as UCB and UCB1, and develop a meta-algorithm called ESBAS. By the end of the book, you'll have worked with key RL algorithms to overcome challenges in real-world applications, and be part of the RL research community.

Who is this book for?

If you are an AI researcher, deep learning user, or anyone who wants to learn reinforcement learning from scratch, this book is for you. You’ll also find this reinforcement learning book useful if you want to learn about the advancements in the field. Working knowledge of Python is necessary.

What you will learn

Develop an agent to play CartPole using the OpenAI Gym interface
Discover the model-based reinforcement learning paradigm
Solve the Frozen Lake problem with dynamic programming
Explore Q-learning and SARSA with a view to playing a taxi game
Apply Deep Q-Networks (DQNs) to Atari games using Gym
Study policy gradient algorithms, including Actor-Critic and REINFORCE
Understand and apply PPO and TRPO in continuous locomotion environments
Get to grips with evolution strategies for solving the lunar lander problem

Estimated delivery fee Deliver to Malta

Premium delivery 7 - 10 business days

€32.95

(Includes tracking information)

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Estimated delivery fee Deliver to Malta

Premium delivery 7 - 10 business days

€32.95

(Includes tracking information)

Product Details

Publication date : Oct 18, 2019

Length: 366 pages

Edition : 1st

Language : English

ISBN-13 : 9781789131116

Category :

Data

Languages :

Python

Concepts :

Reinforcement Learning

Tools :

OpenAI Gym

Frequently bought together

Advanced Deep Learning with Python

Dec 2019 468 pages

4.8 (23)

eBook

€8.99 ~~€29.99~~

PyTorch 1.x Reinforcement Learning Cookbook

Oct 2019 340 pages

4.3 (3)

eBook

€8.99 ~~€26.99~~

Reinforcement Learning Algorithms with Python

Oct 2019 366 pages

3 (3)

eBook

€8.99 ~~€23.99~~

Total € 99.97

€36.99

€32.99

€29.99

Total € 99.97

18 Chapters

Section 1: Algorithms and Environments

The Landscape of Reinforcement Learning

An introduction to RL

Implementing RL Cycle and OpenAI Gym

Setting up the environment

OpenAI Gym and RL cycles

Development of ML models using TensorFlow

Introducing TensorBoard

Types of RL environments

Summary

Questions

Further reading

Solving Problems with Dynamic Programming

MDP

Categorizing RL algorithms

Section 2: Model-Free RL Algorithms

Q-Learning and SARSA Applications

Learning without a model

TD learning

SARSA

Applying SARSA to Taxi-v2

Q-learning

Applying Q-learning to Taxi-v2

Summary

Questions

Deep Q-Network

Deep neural networks and Q-learning

Learning Stochastic and PG Optimization

Policy gradient methods

Understanding the REINFORCE algorithm

REINFORCE with baseline

Learning the AC algorithm

Summary

Questions

Further reading

TRPO and PPO Implementation

Roboschool

Natural policy gradient

Trust region policy optimization

Proximal Policy Optimization

Summary

Questions

Further reading

DDPG and TD3 Applications

Combining policy gradient optimization with Q-learning

Deep deterministic policy gradient

Twin delayed deep deterministic policy gradient (TD3)

Summary

Questions

Further reading

Section 3: Beyond Model-Free Algorithms and Improvements

Model-Based RL

Model-based methods

Combining model-based with model-free learning

ME-TRPO applied to an inverted pendulum

Summary

Questions

Further reading

Imitation Learning with the DAgger Algorithm

Technical requirements

The imitation approach

Playing Flappy Bird

Understanding the dataset aggregation algorithm

Understanding Black-Box Optimization Algorithms

Beyond RL

The core of EAs

Scalable evolution strategies

Applying scalable ES to LunarLander

Summary

Questions

Further reading

Developing the ESBAS Algorithm

Exploration versus exploitation

Approaches to exploration

Epochal stochastic bandit algorithm selection

Summary

Questions

Further reading

Practical Implementation for Resolving RL Challenges

Best practices of deep RL

Challenges in deep RL

Advanced techniques

RL in the real world

Future of RL and its impact on society

Summary

Questions

Further reading

Assessments

Other Books You May Enjoy

Leave a review - let other readers know what you think

Recommendations for you

Python Machine Learning By Example

Jul 2024 518 pages

4.9 (8)

eBook

€8.99 ~~€27.99~~

Unlocking Data with Generative AI and RAG

Sep 2024 346 pages

eBook

€8.99 ~~€23.99~~

Building LLM Powered Applications

May 2024 342 pages

4.2 (22)

eBook

€8.99 ~~€29.99~~

Python for Algorithmic Trading Cookbook

Aug 2024 404 pages

4.6 (15)

eBook

€8.99 ~~€35.99~~

Machine Learning with PyTorch and Scikit-Learn

Feb 2022 774 pages

4.4 (95)

eBook

€8.99 ~~€32.99~~

Artificial Intelligence Engines

Nov 2024 217 pages

eBook

€4.99 ~~€7.99~~

AI Product Manager's Handbook

Nov 2024 484 pages

eBook

€8.99 ~~€29.99~~

RAG-Driven Generative AI

Sep 2024 334 pages

4.5 (13)

eBook

€8.99 ~~€32.99~~

Hands-On Reinforcement Learning with Python

Jun 2018 318 pages

2.6 (18)

eBook

€8.99 ~~€23.99~~

LLM Engineer's Handbook

Oct 2024 522 pages

4.9 (15)

eBook

€8.99 ~~€43.99~~

Customer reviews

Rating distribution

(3 Ratings)

5 star 33.3%

4 star 0%

3 star 33.3%

2 star 0%

1 star 33.3%

Sebastien Feb 16, 2020

Easy to understand and in each chapter there is an example, with code, that help you understand how to actually use the algorithm

Amazon Verified review

schwarzwald Apr 12, 2020

Good content but doesn't mention that Tensorflow 1 is required. The book uses code that will not work in the current TF version. For people not intimately familiar with TF 1 vs. 2, this will be confusing.

Amazon Verified review

designer Mar 16, 2023

Non of the code samples in the book and code samples in GitHub work because they are outdated. The code showed 4 years ago and the author hasn’t updated them. When I copied the samples, they all kept saying outdated and a bunch of other errors due to solfware incompatible. Wasted time and money

Amazon Verified review

People who bought this also bought

Machine Learning Engineering with Python

Aug 2023 462 pages

4.6 (36)

eBook

€8.99 ~~€29.99~~

Deep Learning with TensorFlow and Keras – 3rd edition

Oct 2022 698 pages

4.6 (45)

eBook

€8.99 ~~€29.99~~

Modern Generative AI with ChatGPT and OpenAI Models

May 2023 286 pages

4.2 (34)

eBook

€8.99 ~~€29.99~~

Generative AI with LangChain

Dec 2023 368 pages

4 (34)

eBook

€8.99 ~~€29.99~~

Causal Inference and Discovery in Python

May 2023 456 pages

4.5 (49)

eBook

€8.99 ~~€23.99~~

About the author

Lonza

Andrea Lonza is a deep learning engineer with a great passion for artificial intelligence and a desire to create machines that act intelligently. He has acquired expert knowledge in reinforcement learning, natural language processing, and computer vision through academic and industrial machine learning projects. He has also participated in several Kaggle competitions, achieving high results. He is always looking for compelling challenges and loves to prove himself.

See other products by Lonza

FAQs

What is the delivery time and cost of print book?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

What is custom duty/charge?

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order?

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges?

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.

How can I cancel my order?

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy?

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged?

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use?

You can pay with the following card types:

Visa Debit
Visa Credit
MasterCard
PayPal

What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges

What do you get with Print?