Procedural Content Generation in Games

Procedural Content Generation in Games PDF Author: Noor Shaker
Publisher: Springer
ISBN: 3319427164
Category : Computers
Languages : en
Pages : 247

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Book Description
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 in Games

Procedural Content Generation in Games PDF Author: Noor Shaker
Publisher: Springer
ISBN: 3319427164
Category : Computers
Languages : en
Pages : 247

Get Book Here

Book Description
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

Procedural Content Generation via Machine Learning PDF Author: Matthew Guzdial
Publisher: Springer Nature
ISBN: 3031167198
Category : Computers
Languages : en
Pages : 246

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Book Description
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.

General Video Game Artificial Intelligence

General Video Game Artificial Intelligence PDF Author: Diego Pérez Liébana
Publisher: Morgan & Claypool Publishers
ISBN: 1681736454
Category : Computers
Languages : en
Pages : 193

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Book Description
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.

Artificial Intelligence and Games

Artificial Intelligence and Games PDF Author: Georgios N. Yannakakis
Publisher: Springer
ISBN: 3319635190
Category : Computers
Languages : en
Pages : 350

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Book Description
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.

Applications of Evolutionary Computation

Applications of Evolutionary Computation PDF Author: Cecilia Di Chio
Publisher: Springer
ISBN: 3642122396
Category : Computers
Languages : en
Pages : 644

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Book Description
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.

Augmented Reality, Virtual Reality, and Computer Graphics

Augmented Reality, Virtual Reality, and Computer Graphics PDF Author: Lucio Tommaso De Paolis
Publisher: Springer Nature
ISBN: 3030584658
Category : Computers
Languages : en
Pages : 489

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Book Description
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.

Advances in Machine Learning/Deep Learning-based Technologies

Advances in Machine Learning/Deep Learning-based Technologies PDF Author: George A. Tsihrintzis
Publisher: Springer Nature
ISBN: 3030767949
Category : Technology & Engineering
Languages : en
Pages : 237

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Book Description
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.

Procedural Content Generation for C++ Game Development

Procedural Content Generation for C++ Game Development PDF Author: Dale Green
Publisher: Packt Publishing Ltd
ISBN: 1785886355
Category : Computers
Languages : en
Pages : 304

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Book Description
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 Generation in Game Design

Procedural Generation in Game Design PDF Author: Tanya Short
Publisher: CRC Press
ISBN: 1498799205
Category : Computers
Languages : en
Pages : 339

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Book Description
Making a game can be an intensive process, and if not planned accurately can easily run over budget. The use of procedural generation in game design can help with the intricate and multifarious aspects of game development; thus facilitating cost reduction. This form of development enables games to create their play areas, objects and stories based on a set of rules, rather than relying on the developer to handcraft each element individually. Readers will learn to create randomized maps, weave accidental plotlines, and manage complex systems that are prone to unpredictable behavior. Tanya Short’s and Tarn Adams’ Procedural Generation in Game Design offers a wide collection of chapters from various experts that cover the implementation and enactment of procedural generation in games. Designers from a variety of studios provide concrete examples from their games to illustrate the many facets of this emerging sub-discipline. Key Features: Introduces the differences between static/traditional game design and procedural game design Demonstrates how to solve or avoid common problems with procedural game design in a variety of concrete ways Includes industry leaders’ experiences and lessons from award-winning games World’s finest guide for how to begin thinking about procedural design

Handbook of Evolutionary Machine Learning

Handbook of Evolutionary Machine Learning PDF Author: Wolfgang Banzhaf
Publisher: Springer Nature
ISBN: 9819938147
Category : Computers
Languages : en
Pages : 764

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Book Description
This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains. This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.