June 2018
Intermediate to advanced
204 pages
4h 40m
English
Overview
"Learn Unity ML-Agents: Fundamentals of Unity Machine Learning" introduces developers to the exciting world of integrating machine learning with game development using Unity. Through this book, you will understand how Reinforcement Learning and Deep Learning can be used to create intelligent agents for simulations and games, and gain hands-on experience applying these concepts using Unity ML-Agents.
What this Book will help me do
- Understand and apply fundamental principles of Reinforcement and Q-Learning algorithms.
- Implement intelligent agents with neural networks using Python and TensorFlow.
- Learn how to adapt existing Unity components for machine learning, like Academy and Agents.
- Master techniques to develop cooperative and competitive multi-agent systems.
- Explore advanced training scenarios such as A3C and curriculum learning methods.
Author(s)
The author of "Learn Unity ML-Agents," an experienced software developer and educator, specializes in artificial intelligence applications and game development. With hands-on expertise in Python, machine learning algorithms, and Unity, they bring practical insights and clear explanations to complex topics. They are passionate about teaching programming and AI techniques to empower learners and professionals alike.
Who is it for?
This book is ideal for game developers and researchers who are passionate about incorporating AI into their simulations and games. It provides value to those with an intermediate understanding of C programming and a basic familiarity with Python and neural network concepts. If you aim to enhance your skill set with Reinforcement Learning and develop AI-driven projects in Unity, this book is for you.
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