Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Hands-On Reinforcement Learning for Games

You're reading from Hands-On Reinforcement Learning for Games Implementing self-learning agents in games using artificial intelligence techniques

Product type Paperback

Published in Jan 2020

Publisher Packt

ISBN-13 9781839214936

Length 432 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

Micheal Lanham

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Exploring the Environment

2. Understanding Rewards-Based Learning FREE CHAPTER

3. Dynamic Programming and the Bellman Equation

4. Monte Carlo Methods

5. Temporal Difference Learning

6. Exploring SARSA

7. Section 2: Exploiting the Knowledge

8. Going Deep with DQN

9. Going Deeper with DDQN

10. Policy Gradient Methods

11. Optimizing for Continuous Control

12. All about Rainbow DQN

13. Exploiting ML-Agents

14. DRL Frameworks

15. Section 3: Reward Yourself

16. 3D Worlds

17. From DRL to AGI

18. Other Books You May Enjoy

Leave a review - let other readers know what you think

Who this book is for

This book is for game developers who are looking to add to their knowledge by implementing RL techniques to build games from scratch. This book will also appeal to machine learning and deep learning practitioners, and RL researchers who want to understand how self-learning agents can be used in the game domain. Prior knowledge of game development and a working knowledge of Python programming are expected.

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 $19.99/month. Cancel anytime

Authors (1)

Micheal Lanham

Micheal Lanham

Micheal Lanham is a proven software and tech innovator with 20 years of experience. During that time, he has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries as an R&D developer. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development. He was later introduced to Unity and has been an avid developer, consultant, manager, and author of multiple Unity games, graphic projects, and books ever since.

See other products by Micheal Lanham

Other recommended products

Related to this chapter

Hands-On Deep Learning for Games

Hands-On Deep Learning for Games

This book will give you an in-depth view of the potential of deep learning and neural networks in game development. You will also learn to use neural nets combined with reinforcement learning for new types of game AI.

Mar 2019 13h 4m

Hands-On Deep Learning for Games

Hands-On Deep Learning for Games

This book will give you an in-depth view of the potential of deep learning and neural networks in game development. You will also learn to use neural nets combined with reinforcement learning for new types of game AI.

Mar 2019 13h 4m

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 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.

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Unity Machine Learning Agents allows researchers and developers to create games and simulations using the Unity Editor which serve as environments where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multiagent ecosystem.

Jun 2018 6h 48m

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Unity Machine Learning Agents allows researchers and developers to create games and simulations using the Unity Editor which serve as environments where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multiagent ecosystem.

Jun 2018 6h 48m

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Unity Machine Learning Agents allows researchers and developers to create games and simulations using the Unity Editor which serve as environments where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multiagent ecosystem.

Jun 2018 6h 48m

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.

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.

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.

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Personalised recommendations for you

Based on your interests and search pattern

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Realizing 3D Animation in Blender

Realizing 3D Animation in Blender

Learn Blender and animation at the same time! With clearly explained exercises, insightful commentary, and a focus on animation, this book has everything you need to start animating with the world's most advanced free software for 3D content creation.

Jul 2024 15h 12m

Unity 2022 by Example

Unity 2022 by Example

This book will introduce you to C# concepts and programming patterns in Unity that will help you solve common problems. After working on a range of 2D, 3D, AR, and VR game projects, you'll be able to confidently build playable and commercial games.

Jun 2024 19h 52m

Unity 2022 by Example

Unity 2022 by Example

This book will introduce you to C# concepts and programming patterns in Unity that will help you solve common problems. After working on a range of 2D, 3D, AR, and VR game projects, you'll be able to confidently build playable and commercial games.

Jun 2024 19h 52m

Unity 2022 by Example

Unity 2022 by Example

This book will introduce you to C# concepts and programming patterns in Unity that will help you solve common problems. After working on a range of 2D, 3D, AR, and VR game projects, you'll be able to confidently build playable and commercial games.

Jun 2024 19h 52m

Unity 2022 by Example

Unity 2022 by Example

This book will introduce you to C# concepts and programming patterns in Unity that will help you solve common problems. After working on a range of 2D, 3D, AR, and VR game projects, you'll be able to confidently build playable and commercial games.

Jun 2024 19h 52m

Unity 2022 by Example

Unity 2022 by Example

This book will introduce you to C# concepts and programming patterns in Unity that will help you solve common problems. After working on a range of 2D, 3D, AR, and VR game projects, you'll be able to confidently build playable and commercial games.

Jun 2024 19h 52m