Learn Unity Ml Agents Fundamentals Of Unity Machine Learning

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Learn Unity ML-Agents – Fundamentals of Unity Machine Learning

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
ISBN 13 : 1789131863
Total Pages : 197 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Learn Unity ML-Agents – Fundamentals of Unity Machine Learning by : Micheal Lanham

Download or read book Learn Unity ML-Agents – Fundamentals of Unity Machine Learning written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2018-06-30 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Abhilash Majumder
Publisher : Apress
ISBN 13 : 9781484265024
Total Pages : 530 pages
Book Rating : 4.2/5 (65 download)

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Book Synopsis Deep Reinforcement Learning in Unity by : Abhilash Majumder

Download or read book Deep Reinforcement Learning in Unity written by Abhilash Majumder and published by Apress. This book was released on 2020-12-02 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hands-On Reinforcement Learning for Games

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
ISBN 13 : 1839216778
Total Pages : 420 pages
Book Rating : 4.8/5 (392 download)

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Book Synopsis Hands-On Reinforcement Learning for Games by : Micheal Lanham

Download or read book Hands-On Reinforcement Learning for Games written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2020-01-03 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key FeaturesGet to grips with the different reinforcement and DRL algorithms for game developmentLearn how to implement components such as artificial agents, map and level generation, and audio generationGain insights into cutting-edge RL research and understand how it is similar to artificial general researchBook Description With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python. Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent’s productivity. As you advance, you’ll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games. By the end of this book, you’ll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications. What you will learnUnderstand how deep learning can be integrated into an RL agentExplore basic to advanced algorithms commonly used in game developmentBuild agents that can learn and solve problems in all types of environmentsTrain a Deep Q-Network (DQN) agent to solve the CartPole balancing problemDevelop game AI agents by understanding the mechanism behind complex AIIntegrate all the concepts learned into new projects or gaming agentsWho this book is for If you’re a game developer looking to implement AI techniques to build next-generation games from scratch, this book is for you. Machine learning and deep learning practitioners, and RL researchers who want to understand how to use self-learning agents in the game domain will also find this book useful. Knowledge of game development and Python programming experience are required.

Hands-On Deep Learning for Games

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
ISBN 13 : 1788998766
Total Pages : 379 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Deep Learning for Games by : Micheal Lanham

Download or read book Hands-On Deep Learning for Games written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key FeaturesApply the power of deep learning to complex reasoning tasks by building a Game AIExploit the most recent developments in machine learning and AI for building smart gamesImplement deep learning models and neural networks with PythonBook Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning. What you will learnLearn the foundations of neural networks and deep learning.Use advanced neural network architectures in applications to create music, textures, self driving cars and chatbots. Understand the basics of reinforcement and DRL and how to apply it to solve a variety of problems.Working with Unity ML-Agents toolkit and how to install, setup and run the kit.Understand core concepts of DRL and the differences between discrete and continuous action environments.Use several advanced forms of learning in various scenarios from developing agents to testing games.Who this book is for This books is for game developers who wish to create highly interactive games by leveraging the power of machine and deep learning. No prior knowledge of machine learning, deep learning or neural networks is required this book will teach those concepts from scratch. A good understanding of Python is required.

Game Audio Development with Unity 5.X

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
ISBN 13 : 1787120805
Total Pages : 394 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Game Audio Development with Unity 5.X by : Micheal Lanham

Download or read book Game Audio Development with Unity 5.X written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create 'AAA' quality game audio with new features and tools built for Unity About This Book Explore the basics of audio development in Unity to create spatial sound, mixing, effects, composition, adaptive audio and more. Leverage the Audio Mixer of Unity 5.x to create blockbuster sound and music for your game. Learn about developing professional audio for games with FMOD Studio and composing original music with Reaper. Build amazing audio synchronized graphic visualizations with Unity. Understand how real-time character lip syncing can be implemented. Who This Book Is For The ideal target audience for this book will be game developers, both Indie as well as semi pro. No prior knowledge of Unity and audio development is assumed, What You Will Learn Develop game audio and other audio effects with Unity Getting familiar with the new Audio Mixer introduced in Unity 5 Implement dynamic and adaptive audio using various tools and strategies Explore interesting ways to incorporate audio into a game with sound visualization Use 3rd party professional audio development tools like FMOD Compose original music and record vocals Understand and troubleshoot audio performance issues In Detail Game Audio is one of the key components in making a game successful and it is quite popular in the gaming industry. So if you are a game developer with an eye on capturing the gamer market then this book is the right solution for you. In this book, we will take you through a step by step journey which will teach you to implement original and engaging soundtracks and SFX with Unity 5.x. You will be firstly introduced to the basics of game audio and sound development in Unity. After going through the core topics of audio development: audio sources, spatial sound, mixing, effects, and more; you will then have the option of delving deeper into more advanced topics like dynamic and adaptive audio. You will also learn to develop dynamic and adaptive audio using the Unity Audio Mixer. Further, you will learn how professional third party tools like FMOD are used for audio development in Unity. You will then go through the creation of sound visualization techniques and creating your own original music using the simple yet powerful audio workstation Reaper. Lastly, you will go through tips, techniques and strategies to help you optimize game audio performance or troubleshoot issues. At the end of the book, you'll have gained the skills to implement professional sound and music. Along with a good base knowledge audio and music principles you can apply across a range of other game development tools. Style and approach This book will have a step by step practical approach where downloadable free games will be given with the book and readers will be free to work with them.

Introduction to Unity ML-Agents

Author : Dylan Engelbrecht
Publisher :
ISBN 13 : 9781484289990
Total Pages : 0 pages
Book Rating : 4.2/5 (899 download)

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Book Synopsis Introduction to Unity ML-Agents by : Dylan Engelbrecht

Download or read book Introduction to Unity ML-Agents written by Dylan Engelbrecht and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Foundations of Deep Reinforcement Learning

Author : Laura Graesser
Publisher : Addison-Wesley Professional
ISBN 13 : 0135172489
Total Pages : 625 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Foundations of Deep Reinforcement Learning by : Laura Graesser

Download or read book Foundations of Deep Reinforcement Learning written by Laura Graesser and published by Addison-Wesley Professional. This book was released on 2019-11-20 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Practical AI on the Google Cloud Platform

Author : Micheal Lanham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492075760
Total Pages : 394 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical AI on the Google Cloud Platform by : Micheal Lanham

Download or read book Practical AI on the Google Cloud Platform written by Micheal Lanham and published by "O'Reilly Media, Inc.". This book was released on 2020-10-20 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI and AutoML Tables Build a simple language processor using deep learning systems Perform image recognition using CNNs, transfer learning, and GANs Use Google's Dialogflow to create chatbots and conversational AI Analyze video with automatic video indexing, face detection, and TensorFlow Hub Build a complete working AI agent application

Augmented Reality with Unity AR Foundation

Author : Jonathan Linowes
Publisher : Packt Publishing Ltd
ISBN 13 : 1838982965
Total Pages : 383 pages
Book Rating : 4.8/5 (389 download)

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Book Synopsis Augmented Reality with Unity AR Foundation by : Jonathan Linowes

Download or read book Augmented Reality with Unity AR Foundation written by Jonathan Linowes and published by Packt Publishing Ltd. This book was released on 2021-08-16 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the world of augmented reality development with the latest features of Unity and step-by-step tutorial-style examples with easy-to-understand explanations Key FeaturesBuild functional and interactive augmented reality applications using the Unity 3D game engineLearn to use Unity's XR and AR components, including AR Foundation and other standard Unity featuresImplement common AR application user experiences needed to build engaging applicationsBook Description Augmented reality applications allow people to interact meaningfully with the real world through digitally enhanced content. The book starts by helping you set up for AR development, installing the Unity 3D game engine, required packages, and other tools to develop for Android (ARCore) and/or iOS (ARKit) mobile devices. Then we jump right into the building and running AR scenes, learning about AR Foundation components, other Unity features, C# coding, troubleshooting, and testing. We create a framework for building AR applications that manages user interaction modes, user interface panels, and AR onboarding graphics that you will save as a template for reuse in other projects in this book. Using this framework, you will build multiple projects, starting with a virtual photo gallery that lets you place your favorite framed photos on your real-world walls, and interactively edit these virtual objects. Other projects include an educational image tracking app for exploring the solar system, and a fun selfie app to put masks and accessories on your face. The book provides practical advice and best practices that will have you up and running quickly. By the end of this AR book, you will be able to build your own AR applications, engaging your users in new and innovative ways. What you will learnDiscover Unity engine features for building AR applications and gamesGet up to speed with Unity AR Foundation components and the Unity APIBuild a variety of AR projects using best practices and important AR user experiencesUnderstand the core concepts of augmented reality technology and development for real-world projectsSet up your system for AR development and learn to improve your development workflowCreate an AR user framework with interaction modes and UI, saved as a template for new projectsWho this book is for This augmented reality book is for game developers interested in adding AR capabilities to their games and apps. The book assumes beginner-level knowledge of Unity development and C# programming, familiarity with 3D graphics, and experience in using existing AR applications. Beginner-level experience in developing mobile applications will be helpful to get the most out of this AR Unity book.

Artificial Intelligence and Games

Author : Georgios N. Yannakakis
Publisher : Springer
ISBN 13 : 3319635190
Total Pages : 337 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Artificial Intelligence and Games by : Georgios N. Yannakakis

Download or read book Artificial Intelligence and Games written by Georgios N. Yannakakis and published by Springer. This book was released on 2018-02-17 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.

Entertainment Computing and Serious Games

Author : Erik van der Spek
Publisher : Springer Nature
ISBN 13 : 3030346447
Total Pages : 490 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Entertainment Computing and Serious Games by : Erik van der Spek

Download or read book Entertainment Computing and Serious Games written by Erik van der Spek and published by Springer Nature. This book was released on 2019-11-07 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

C# Machine Learning Projects

Author : Yoon Hyup Hwang
Publisher :
ISBN 13 : 9781788996402
Total Pages : 350 pages
Book Rating : 4.9/5 (964 download)

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Book Synopsis C# Machine Learning Projects by : Yoon Hyup Hwang

Download or read book C# Machine Learning Projects written by Yoon Hyup Hwang and published by . This book was released on 2018-06-14 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power your C# and .NET applications with exciting machine learning models and modular projects Key Features Produce classification, regression, association, and clustering models Expand your understanding of machine learning and C# Get to grips with C# packages such as Accord.net, LiveCharts, and Deedle Book Description Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising; from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects. You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections. By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects. What you will learn Set up the C# environment for machine learning with required packages Build classification models for spam email filtering Get to grips with feature engineering using NLP techniques for Twitter sentiment analysis Forecast foreign exchange rates using continuous and time-series data Make a recommendation model for music genre recommendation Familiarize yourself with munging image data and Neural Network models for handwritten-digit recognition Use Principal Component Analysis (PCA) for cyber attack detection One-Class Support Vector Machine for credit card fraud detection Who this book is for If you're a C# or .NET developer with good knowledge of C#, then this book is perfect for you to get Machine Learning into your projects and make smarter applications.

Entertainment Computing – ICEC 2021

Author : Jannicke Baalsrud Hauge
Publisher : Springer Nature
ISBN 13 : 3030893944
Total Pages : 549 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Entertainment Computing – ICEC 2021 by : Jannicke Baalsrud Hauge

Download or read book Entertainment Computing – ICEC 2021 written by Jannicke Baalsrud Hauge and published by Springer Nature. This book was released on 2021-10-31 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Democratization of Artificial Intelligence

Author : Andreas Sudmann
Publisher : transcript Verlag
ISBN 13 : 3839447194
Total Pages : 335 pages
Book Rating : 4.8/5 (394 download)

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Book Synopsis The Democratization of Artificial Intelligence by : Andreas Sudmann

Download or read book The Democratization of Artificial Intelligence written by Andreas Sudmann and published by transcript Verlag. This book was released on 2019-10-31 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?

Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1

Author : Kohei Arai
Publisher : Springer Nature
ISBN 13 : 3031184610
Total Pages : 948 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1 by : Kohei Arai

Download or read book Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1 written by Kohei Arai and published by Springer Nature. This book was released on 2022-10-12 with total page 948 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seventh Future Technologies Conference 2022 was organized in a hybrid mode. It received a total of 511 submissions from learned scholars, academicians, engineers, scientists and students across many countries. The papers included the wide arena of studies like Computing, Artificial Intelligence, Machine Vision, Ambient Intelligence and Security and their jaw- breaking application to the real world. After a double-blind peer review process 177 submissions have been selected to be included in these proceedings. One of the prominent contributions of this conference is the confluence of distinguished researchers who not only enthralled us by their priceless studies but also paved way for future area of research. The papers provide amicable solutions to many vexing problems across diverse fields. They also are a window to the future world which is completely governed by technology and its multiple applications. We hope that the readers find this volume interesting and inspiring and render their enthusiastic support towards it.

Artificial General Intelligence

Author : Ben Goertzel
Publisher : Springer Nature
ISBN 13 : 3030937585
Total Pages : 379 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Artificial General Intelligence by : Ben Goertzel

Download or read book Artificial General Intelligence written by Ben Goertzel and published by Springer Nature. This book was released on 2022-01-06 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Artificial General Intelligence, AGI 2021, held as a hybrid event in San Francisco, CA, USA, in October 2021. The 36 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.

Learn Arcore - Fundamentals of Google Arcore

Author : Micheal Lanham
Publisher : Packt Publishing
ISBN 13 : 9781788830409
Total Pages : 274 pages
Book Rating : 4.8/5 (34 download)

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Book Synopsis Learn Arcore - Fundamentals of Google Arcore by : Micheal Lanham

Download or read book Learn Arcore - Fundamentals of Google Arcore written by Micheal Lanham and published by Packt Publishing. This book was released on 2018-03-30 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create next-generation Augmented Reality and Mixed Reality apps with the latest version of Google ARCore Key Features Harness the power of the Google's new augmented reality (AR) platform ARCore to build cutting-edge Augmented reality apps Learn core concepts of Environmental Understanding, Immersive Computing, and Motion Tracking with ARCore Extend your application by combining ARCore with OpenGL, Machine Learning and more. Book Description Are you a mobile developer or web developer who wants to create immersive and cool Augmented Reality apps with the latest Google ARCore platform? If so, this book will help you jump right into developing with ARCore and will help you create a step by step AR app easily. This book will teach you how to implement the core features of ARCore starting from the fundamentals of 3D rendering to more advanced concepts such as lighting, shaders, Machine Learning, and others. We'll begin with the basics of building a project on three platforms: web, Android, and Unity. Next, we'll go through the ARCore concepts of motion tracking, environmental understanding, and light estimation. For each core concept, you'll work on a practical project to use and extend the ARCore feature, from learning the basics of 3D rendering and lighting to exploring more advanced concepts. You'll write custom shaders to light virtual objects in AR, then build a neural network to recognize the environment and explore even grander applications by using ARCore in mixed reality. At the end of the book, you'll see how to implement motion tracking and environment learning, create animations and sounds, generate virtual characters, and simulate them on your screen. What you will learn Build and deploy your Augmented Reality app to the Android, Web, and Unity platforms Implement ARCore to identify and visualize objects as point clouds, planes, surfaces, and/or meshes Explore advanced concepts of environmental understanding using Google ARCore and OpenGL ES with Java Create light levels from ARCore and create a C# script to watch and propagate lighting changes in a scene Develop graphics shaders that react to changes in lighting and map the environment to place objects in Unity/C# Integrate motion tracking with the Web ARCore API and Google Street View to create a combined AR/VR experience Who this book is for This book is for web and mobile developers who have broad programming knowledge on Java or JavaScript or C# and want to develop Augmented Reality applications with Google ArCore. To follow this book no prior experience with AR development, 3D, or 3D math experience is needed.