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: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games

bTransform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity/bh2About This Book/h2ulliLearn how to apply core machine learning concepts to your games with Unity/liliLearn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your...

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Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Lanham, Micheal (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Birmingham Packt Publishing Limited 2018
Ausgabe:1
Schlagworte:
COMPUTERS / Programming / Games
COMPUTERS / Intelligence (AI) &amp
Semantics
Online-Zugang:UER01
Zusammenfassung:bTransform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity/bh2About This Book/h2ulliLearn how to apply core machine learning concepts to your games with Unity/liliLearn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your games/liliLearn How to build multiple asynchronous agents and run them in a training scenario/li/ulh2Who This Book Is For/h2This 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.h2What You Will Learn/h2ulliDevelop Reinforcement and Deep Reinforcement Learning for games./liliUnderstand complex and advanced concepts of reinforcement learning and neural networks/liliExplore various training strategies for cooperative and competitive agent development/liliAdapt the basic script components of Academy, Agent,
and Brain to be used with Q Learning./liliEnhance the Q Learning model with improved training strategies such as Greedy-Epsilon exploration/liliImplement a simple NN with Keras and use it as an external brain in Unity/liliUnderstand how to add LTSM blocks to an existing DQN/liliBuild multiple asynchronous agents and run them in a training scenario/li/ulh2In Detail/h2Unity 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.h2Style and approach/h2This book focuses on the foundations of ML, RL and DL for building agents in a game or simulation
Beschreibung:1 Online-Ressource (204 Seiten)
ISBN:9781789131864

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