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
Автор: Abhilash Majumder
Издательство: Apress
Год: 2021
Страниц: 572
Язык: английский
Формат: pdf (true), epub
Размер: 33.4 MB
Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity. This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn аbout: deep learning and work through an introduction to Tensorflow for writing neural networks