Learn Unity ML-Agents – Fundamentals of Unity Machine Learning · Incorporate New Powerful ML Algorithms Such as Deep Reinforcement Learning for Games

Learn Unity ML - Agents - Fundamentals of Unity Machine Learning

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and UnityKey Features: *Learn how to apply core machine learning concepts to your games with Unity* Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your games* Learn How to build multiple asynchronous agents and run them in a training scenarioBook DescriptionUnity Machine Learning agents allow researchers and developers to create games and simulations using the Unity Editor, which serves as an environment 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 multi-agent ecosystem. You will start with the basics of Reinforcement Learning and how to apply it to problems. Then you will learn how to build self-learning advanced neural networks with Python and Keras/TensorFlow. From there you move o n to more advanced training scenarios where you will learn further innovative ways to train your network with A3C, imitation, and curriculum learning models. By the end of the book, you will have learned how to build more complex environments by building a cooperative and competitive multi-agent ecosystem.