Learn Unity ML-Agents – Fundamentals of Unity Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Learn Unity ML-Agents – Fundamentals of Unity Machine Learning write by Micheal Lanham. This book was released on 2018-06-30. Learn Unity ML-Agents – Fundamentals of Unity Machine Learning available in PDF, EPUB and Kindle. Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity Key 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 scenario Book Description 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. 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. What you will learn Develop Reinforcement and Deep Reinforcement Learning for games. Understand complex and advanced concepts of reinforcement learning and neural networks Explore various training strategies for cooperative and competitive agent development Adapt the basic script components of Academy, Agent, and Brain to be used with Q Learning. Enhance the Q Learning model with improved training strategies such as Greedy-Epsilon exploration Implement a simple NN with Keras and use it as an external brain in Unity Understand how to add LTSM blocks to an existing DQN Build multiple asynchronous agents and run them in a training scenario Who this book is for 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.
Deep Reinforcement Learning in Unity
Deep Reinforcement Learning in Unity - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Reinforcement Learning in Unity write by Abhilash Majumder. This book was released on 2020-12-02. Deep Reinforcement Learning in Unity available in PDF, EPUB and Kindle. 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 for training Agent Brain in the context of Unity ML Agents Create different models and perform hyper-parameter tuning Understand the Brain-Academy architecture in Unity ML Agents Understand the Python-C# API interface during real-time training of neural networks Grasp the fundamentals of generic neural networks and their variants using Tensorflow Create simulations and visualize agents playing games in Unity Who This Book Is For Readers with preliminary programming and game development experience in Unity, and those with experience in Python and a general idea of machine learning
Introduction to Unity ML-Agents
Introduction to Unity ML-Agents - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Unity ML-Agents write by Dylan Engelbrecht. This book was released on 2023. Introduction to Unity ML-Agents available in PDF, EPUB and Kindle. Demystify the creation of efficient AI systems using the model-based reinforcement learning Unity ML-Agents - a powerful bridge between the world of Unity and Python. We will start with an introduction to the field of AI, then discuss the progression of AI and where we are today. We will follow this up with a discussion of moral and ethical considerations. You will then learn how to use the powerful machine learning tool and investigate different potential real-world use cases. We will examine how AI agents perceive the simulated world and how to use inputs, outputs, and rewards to train efficient and effective neural networks. Next, you'll learn how to use Unity ML-Agents and how to incorporate them into your game or product. This book will thoroughly introduce you to ML-Agents in Unity and how to use them in your next project. You will: Understand machine learning, its history, capabilities, and expected progression Gain a step-by-step guide to creating your first AI Work with challenges of varying difficulty, along with tips to reinforce concepts covered Master broad concepts within AI.
Entertainment Computing and Serious Games
Entertainment Computing and Serious Games - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Entertainment Computing and Serious Games write by Erik van der Spek. This book was released on 2019-11-07. Entertainment Computing and Serious Games available in PDF, EPUB and Kindle. This book constitutes the refereed proceedings of the First IFIP TC 14 Joint International Conference on Entertainment Computing and Serious Games, ICEC-JCSG 2019, held in Arequipa, Peru, in November 2019. The 26 full papers, 5 short papers, and 16 poster, demonstration, and workshop papers presented were carefully reviewed and selected from 88 submissions. They cover a large range of topics at the multidisciplinary intersection of design, art, entertainment, interaction, computing, psychology, and numerous serious application domains. The papers are organized in the following topical sections: mixed reality; virtual reality; entertainment algorithms; game design and development; interaction technologies; measurement and effects; and serious game applications.
Entertainment Computing – ICEC 2021
Entertainment Computing – ICEC 2021 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Entertainment Computing – ICEC 2021 write by Jannicke Baalsrud Hauge. This book was released on 2021-10-31. Entertainment Computing – ICEC 2021 available in PDF, EPUB and Kindle. This book constitutes the refereed proceedings of the 20th IFIP TC 14 International Conference on Entertainment Computing, ICEC 2021, which was supposed to take place in Coimbra, Portugal, in November 2021. The 26 full papers, 13 short papers and 11 other papers presented were carefully reviewed and selected from 84 submissions. ICEC brings together researchers and practitioners from diverse backgrounds to discuss the multidisciplinary intersection of design, art, entertainment, interaction, computing, psychology in the fields of gaming and entertainment computing.
