Introduction to Unity ML-Agents: Understand the Interplay of Neural Networks and Simulation Space Using the Unity ML-Agents Package

ISBN-13: 9781484289976 / Angielski / Miękka / 2023 / 190 str.

Dylan Engelbrecht

Opis

Beginner to Intermediate

Demystify the creation of efficient AI systems using the model-based reinforcement learning Unity ML-Agents - a powerful bridge between the world of Unity and Python.We will start with an introduction to the field of AI, then discuss the progression of AI and where we are today. We will follow this up with a discussion of moral and ethical considerations. You will then learn how to use the powerful machine learning tool and investigate different potential real-world use cases. We will examine how AI agents perceive the simulated world and how to use inputs, outputs, and rewards to train efficient and effective neural networks. Next, you'll learn how to use Unity ML-Agents and how to incorporate them into your game or product. This book will thoroughly introduce you to ML-Agents in Unity and how to use them in your next project.
What You Will Learn

• Understand machine learning, its history, capabilities, and expected progression
• Gives a step-by-step guide to creating your first AI
• Presents challenges of varying difficulty, along with tips to reinforce concepts covered
• Broad concepts within AI

Who Is This Book ForTthose interested in machine learning using Unity ML-Agents. To get the best out of this book, you should have a fundamental understanding of C#, some background in Python, and are well versed in Unity.

Spis treści

Chapter 1: Introduction

Sub -Topics:

● About the book

● Required software

Chapter 2: What is Machine Learning?

Sub - Topics

● Introduction to machine learning

● How it’s used currently in the modern day

● Briefly discuss the technologies that power AI

Chapter 3: A History of AI and Where We Are Today

Sub - Topics:

● The first AI

● Early days of computing

● The evolution of AI

● Where we are now

Chapter 4: The Future of AI and Ethical Implications

Sub - Topics:

● Why AI?

● Discussing the moral and ethical implications

● Bias and why we need diverse datasets

● Avoiding a bad future

● The potential for good

● The future of AI

Chapter 5: Flavours of AI

Sub - Topics:

● AI Classification

● Types of AI and what ML-Agents use

● How different AI can solve different real-world challenges

Chapter 6: Dopamine for Machines - The Reward System

Sub - Topics:

● How and when to reward your AI agents

● A good reward system makes for a good AI

● Discuss various techniques for rewarding and punishing AI agents

● Team-based rewards

Chapter 7: Inputs and Outputs

Sub - Topics:

● Inputs

● Using various sensors

● Building a sensor

● Outputs

Chapter 8: Unity ML-Agents

Sub - Topics:

● What is Unity ML-Agents?

● Project and python setup

● What is training and how does it work?

● Exploring the various forms of training

● A snapshot of a trained AI’s brain

Chapter 9: Creating Your First AI in Unity

Sub - Topics:

● Confirming project versions and correct setup

● Introduction to what we’re going to build

● Discussing how we’re going to build it

● Planning the inputs, outputs, and rewards

● Explaining how we’ll leverage these inputs and rewards to get meaningful results

● Setting up the AI Agent and environment

● Create a training environment

● Scaling the training

● Training our first AI

● Reflecting on the data to make improvements

● Training again

● Watching the reader’s first AI become efficient and effective

Chapter 10: Solve a Challenge with AI

Sub - Topics:

● The challenge

● Working through the challenge with the reader

● Tips and advice

Chapter 11: Challenges and Tips

Sub - Topics:

● An easy challenge and tips to solve it

● An intermediate challenge and tips to solve it

Chapter 12: Next Steps

Sub - Topics:

● Where to next?

Chapter 13: Conclusion

Sub - Topics:

● Conclusion

● Thanks

Chapter 14: Final words

O autorze

Dylan Engelbrecht is a Unity gameplay engineer and author of Building Multiplayer Games in Unity: Using Mirror Networking. He has extensive experience in both enterprise and commercial game development. With work showcased by invitation at Comic-Con Africa and rAge Expo, he has an exceptional understanding of all things Unity.

Blurb

Demystify the creation of efficient AI systems using the model-based reinforcement learning Unity ML-Agents - a powerful bridge between the world of Unity and Python.

We will start with an introduction to the field of AI, then discuss the progression of AI and where we are today. We will follow this up with a discussion of moral and ethical considerations. You will then learn how to use the powerful machine learning tool and investigate different potential real-world use cases. We will examine how AI agents perceive the simulated world and how to use inputs, outputs, and rewards to train efficient and effective neural networks. Next, you'll learn how to use Unity ML-Agents and how to incorporate them into your game or product.

This book will thoroughly introduce you to ML-Agents in Unity and how to use them in your next project.

You will:

• Understand machine learning, its history, capabilities, and expected progression

• Gain a step-by-step guide to creating your first AI

• Work with challenges of varying difficulty, along with tips to reinforce concepts covered

• Master broad concepts within AI