Hands-On Reinforcement Learning for Games

3 (2 reviews total)
By Micheal Lanham
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  1. Section 1: Exploring the Environment

About this book

With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python.

Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent’s productivity. As you advance, you’ll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games.

By the end of this book, you’ll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications.

Publication date:
January 2020
Publisher
Packt
Pages
432
ISBN
9781839214936

 

Section 1: Exploring the Environment

Reinforcement Learning (RL) is a complex topic comprising of terminology and concepts that all seem to blend together. In this section, we uncover the terminology and basics of RL for the novice or more advanced user.

This section contains the following chapters:

About the Author

  • 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.

    Browse publications by this author

Latest Reviews

(2 reviews total)
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