Introduction to Unity ML-Agents: Understand the Interplay of Neural Networks and Simulation Space Using the Unity ML-Agents Package
- 2h 5m
- Dylan Engelbrecht
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 For
Tthose 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.
About the Author
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.
In this Book
History of AI and Where We Are Today
The Future of AI and Ethical Implications
Dopamine for Machines
Creating Your First AI in Unity
Solve a Challenge with AI