Learn unity ml agents fundamentals of unity machine learning
Learn Unity ML-Agents Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games by Micheal Lanham
Unity AI - Unity 3D Artificial Intelligence
Learn Unity ML-Agents - Fundamentals of Unity Machine Learning
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Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity. This book is intended for developers with an interest in using Machine learning algorithms to develop better games and simulations with Unity. The reader will be required to have a working knowledge of C and a basic understanding of Python. Unity 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.
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Agents can be trained using reinforcement learning, imitation learning, neuroevolution, or other machine learning methods through a simple-to-use Python API. We collected together the latest resources for you to get started with the SDK. This is a helpful and very accessible session to start learning about ML-Agents. Then, Arthur Juliani, Lead Engineer on ML-Agents explains the workflow in Unity, how the plugin works with a Unity project, the current training methods available, and the latest and upcoming features. Watch the session. Read the post.