Procedural Content Generation Via Machine Learning
DOWNLOAD
Download Procedural Content Generation Via Machine Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Procedural Content Generation Via Machine Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Procedural Content Generation Via Machine Learning
DOWNLOAD
Author : Matthew Guzdial
language : en
Publisher: Springer Nature
Release Date : 2022-12-06
Procedural Content Generation Via Machine Learning written by Matthew Guzdial and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Computers categories.
This book surveys current and future approaches to generating video game content with machine learning or Procedural Content Generation via Machine Learning (PCGML). Machine learning is having a major impact on many industries, including the video game industry. PCGML addresses the use of computers to generate new types of content for video games (game levels, quests, characters, etc.) by learning from existing content. The authors illustrate how PCGML is poised to transform the video games industry and provide the first ever beginner-focused guide to PCGML. This book features an accessible introduction to machine learning topics, and readers will gain a broad understanding of currently employed PCGML approaches in academia and industry. The authors provide guidance on how best to set up a PCGML project and identify open problems appropriate for a research project or thesis. This book is written with machine learning and games novices in mind and includes discussions of practical and ethical considerations along with resources and guidance for starting a new PCGML project.
Procedural Content Generation In Games
DOWNLOAD
Author : Noor Shaker
language : en
Publisher: Springer
Release Date : 2016-10-18
Procedural Content Generation In Games written by Noor Shaker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-18 with Computers categories.
This book presents the most up-to-date coverage of procedural content generation (PCG) for games, specifically the procedural generation of levels, landscapes, items, rules, quests, or other types of content. Each chapter explains an algorithm type or domain, including fractal methods, grammar-based methods, search-based and evolutionary methods, constraint-based methods, and narrative, terrain, and dungeon generation. The authors are active academic researchers and game developers, and the book is appropriate for undergraduate and graduate students of courses on games and creativity; game developers who want to learn new methods for content generation; and researchers in related areas of artificial intelligence and computational intelligence.
Procedural Content Generation Via Machine Learning
DOWNLOAD
Author : Matthew Guzdial
language : en
Publisher: Springer Nature
Release Date : 2025-05-30
Procedural Content Generation Via Machine Learning written by Matthew Guzdial and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Mathematics categories.
This second edition updates and expands upon the first beginner-focused guide to Procedural Content Generation via Machine Learning (PCGML), which is the use of computers to generate new types of content for video games (game levels, quests, characters, etc.) by learning from existing content. The authors survey current and future approaches to generating video game content and illustrate the major impact that PCGML has had on video games industry. In order to provide the most up-to-date information, this new edition incorporates the last two years of research and advancements in this rapidly developing area. The book guides readers on how best to set up a PCGML project and identify open problems appropriate for a research project or thesis. The authors discuss the practical and ethical considerations for PCGML projects and demonstrate how to avoid the common pitfalls. This second edition also introduces a new chapter on Generative AI, which covers the benefits, risks, and methods for applying pre-trained transformers to PCG problems.
Applications Of Evolutionary Computation
DOWNLOAD
Author : Cecilia Di Chio
language : en
Publisher: Springer
Release Date : 2010-04-03
Applications Of Evolutionary Computation written by Cecilia Di Chio and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-03 with Computers categories.
Evolutionary Computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their - ciency and simple underlying principles, these methods can be used for a diverse rangeofactivitiesincludingproblemsolving,optimization,machinelearningand pattern recognition. A large and continuously increasing number of researchers and professionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoApplications 2010, which included a range of events on application-oriented aspects of EC. Since 1998, EvoApplications — formerly known as EvoWorkshops— has provided a unique opportunity for EC researchers to meet and discuss application aspects of EC and has been an important link between EC research and its application in a variety of domains. During these 12 years, new events have arisen, some have disappeared,whileothershavematuredtobecomeconferencesoftheirown,such as EuroGP in 2000, EvoCOP in 2004, and EvoBIO in 2007. And from this year, EvoApplications has become a conference as well.
Procedural Content Generation For C Game Development
DOWNLOAD
Author : Dale Green
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-01-30
Procedural Content Generation For C Game Development written by Dale Green and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-30 with Computers categories.
Get to know techniques and approaches to procedurally generate game content in C++ using Simple and Fast Multimedia Library About This Book This book contains a bespoke Simple and Fast Multimedia Library (SFML) game engine with complete online documentation Through this book, you'll create games that are non-predictable and dynamic and have a high replayability factor Get a breakdown of the key techniques and approaches applied to a real game. Who This Book Is For If you are a game developer who is familiar with C++ and is looking to create bigger and more dynamic games, then this book is for you. The book assumes some prior experience with C++, but any intermediate concepts are clarified in detail. No prior experience with SFML is required. What You Will Learn Discover the systems and ideology that lie at the heart of procedural systems Use Random number generation (RNG) with C++ data types to create random but controlled results Build levels procedurally with randomly located items and events Create dynamic game objects at runtime Construct games using a component-based approach Assemble non-predictable game events and scenarios Operate procedural generation to create dynamic content fast and easily Generate game environments for endless replayability In Detail Procedural generation is a growing trend in game development. It allows developers to create games that are bigger and more dynamic, giving the games a higher level of replayability. Procedural generation isn't just one technique, it's a collection of techniques and approaches that are used together to create dynamic systems and objects. C++ is the industry-standard programming language to write computer games. It's at the heart of most engines, and is incredibly powerful. SFML is an easy-to-use, cross-platform, and open-source multimedia library. Access to computer hardware is broken into succinct modules, making it a great choice if you want to develop cross-platform games with ease. Using C++ and SFML technologies, this book will guide you through the techniques and approaches used to generate content procedurally within game development. Throughout the course of this book, we'll look at examples of these technologies, starting with setting up a roguelike project using the C++ template. We'll then move on to using RNG with C++ data types and randomly scattering objects within a game map. We will create simple console examples to implement in a real game by creating unique and randomised game items, dynamic sprites, and effects, and procedurally generating game events. Then we will walk you through generating random game maps. At the end, we will have a retrospective look at the project. By the end of the book, not only will you have a solid understanding of procedural generation, but you'll also have a working roguelike game that you will have extended using the examples provided. Style and approach This is an easy-to-follow guide where each topic is explained clearly and thoroughly through the use of a bespoke example, then implemented in a real game project.
Procedural Content Generation Via Machine Learning
DOWNLOAD
Author : Matthew Guzdial
language : en
Publisher:
Release Date : 2022
Procedural Content Generation Via Machine Learning written by Matthew Guzdial and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Artificial intelligence categories.
General Video Game Artificial Intelligence
DOWNLOAD
Author : Diego Pérez Liébana
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2019-10-09
General Video Game Artificial Intelligence written by Diego Pérez Liébana and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-09 with Computers categories.
Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.
Augmented Reality Virtual Reality And Computer Graphics
DOWNLOAD
Author : Lucio Tommaso De Paolis
language : en
Publisher: Springer Nature
Release Date : 2020-08-31
Augmented Reality Virtual Reality And Computer Graphics written by Lucio Tommaso De Paolis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-31 with Computers categories.
The 2-volume set LNCS 12242 and 12243 constitutes the refereed proceedings of the 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020, held in Lecce, Italy, in September 2020.* The 45 full papers and 14 short papers presented were carefully reviewed and selected from 99 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, 3D reconstruction visualization, and applications in the areas of cultural heritage, medicine, education, and industry. * The conference was held virtually due to the COVID-19 pandemic.
Game Dynamics
DOWNLOAD
Author : Oliver Korn
language : en
Publisher: Springer
Release Date : 2017-03-29
Game Dynamics written by Oliver Korn and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-29 with Computers categories.
This book offers a compendium of best practices in game dynamics. It covers a wide range of dynamic game elements ranging from player behavior over artificial intelligence to procedural content generation. Such dynamics make virtual worlds more lively and realistic and they also create the potential for moments of amazement and surprise. In many cases, game dynamics are driven by a combination of random seeds, player records and procedural algorithms. Games can even incorporate the player’s real-world behavior to create dynamic responses. The best practices illustrate how dynamic elements improve the user experience and increase the replay value. The book draws upon interdisciplinary approaches; researchers and practitioners from Game Studies, Computer Science, Human-Computer Interaction, Psychology and other disciplines will find this book to be an exceptional resource of both creative inspiration and hands-on process knowledge.
Advances In Machine Learning Deep Learning Based Technologies
DOWNLOAD
Author : George A. Tsihrintzis
language : en
Publisher: Springer Nature
Release Date : 2021-08-05
Advances In Machine Learning Deep Learning Based Technologies written by George A. Tsihrintzis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-05 with Technology & Engineering categories.
As the 4th Industrial Revolution is restructuring human societal organization into, so-called, “Society 5.0”, the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society. The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction. This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.