Bộ sách luyện thi ETS 2023 LC&RC
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299,000₫
Sách Deep Reinforcement Learning in Unity With Unity ML Toolkit (sách keo gáy, bìa mềm)
Categories:Computers
Year:2021
Edition:1
Language:english
Pages:572
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 about: deep learning and
work through an introduction to Tensorflow for writing neural networks
(including perceptron, convolution, and LSTM networks), Q learning with
Unity ML agents, and porting trained neural network models in Unity
through the Python-C# API. You will also explore the OpenAI Gym
Environment used throughout the book.
Deep Reinforcement Learning in Unity provides
a walk-through of the core fundamentals of deep reinforcement learning
algorithms, especially variants of the value estimation, advantage, and
policy gradient algorithms (including the differences between on and off
policy algorithms in reinforcement learning). These core algorithms
include actor critic, proximal policy, and deep deterministic policy
gradients and its variants. And you will be able to write custom neural
networks using the Tensorflow and Keras frameworks.
Deep learning
in games makes the agents learn how they can perform better and collect
their rewards in adverse environments without user interference. The
book provides a thorough overview of integrating ML Agents with Unity
for deep reinforcement learning.
What You Will Learn
Understand how deep reinforcement learning works in games
Grasp the fundamentals of deep reinforcement learning
Integrate these fundamentals with the Unity ML Toolkit SDK
Gain insights into practical neural networks
