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.
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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.
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Introduction.- The Search-Based Approach.- Constructive Generation Methods for Dungeons and Levels.- Fractals, Noise and Agents with Applications to Landscapes and Textures.- Grammars and L-Systems with Applications to Vegetation and Levels.- Rules and Mechanics.- Planning with Applications to Quests and Story.- ASP with Applications to Mazes and Levels.- Representations for Search-Based Methods.- The Experience-Driven Perspective.- Mixed-Initiative Approaches.- Evaluating Content Generators.
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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.
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Procedural Content Generation (PCG) in games is the automatic or computer-assisted generation of content such as levels, landscapes, items, rules, and quests Content class- and industry-tested by leading game developers Hot topic in game development and development and academic game research Includes supplementary material: sn.pub/extras
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GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
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Produktdetaljer

ISBN
9783319427140
Publisert
2016-10-26
Utgiver
Vendor
Springer International Publishing AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Upper undergraduate, P, U, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

Biographical note

Noor Shaker is a postdoctoral researcher in the Center for Applied Game Research in the Dept. of Architecture, Design and Media Technology of Aalborg University Copenhagen (AAU CPH). She was previously a postdoctoral researcher at the Center for Computer Games Research, IT University of Copenhagen. She is the chair of the IEEE CIS Task Force on Player Modeling. Her research interests include player modeling, procedural content generation, computational creativity, affective computing, and player behavior imitation.

Julian Togelius is an associate professor in the Dept. of Computer Science and Engineering of New York University, and a codirector of the NYU Game Innovation Lab. He was previously an Associate Professor at the Center for Computer Games Research, IT University of Copenhagen. He works on all aspects of computational intelligence and games and on selected topics in evolutionary computation and evolutionary reinforcement learning. His current main research directions involve search-based procedural content generation, game adaptation through player modelling, automatic game design, and fair and relevant benchmarking of game AI through competitions. He is a past chair of the IEEE CIS Technical Committee on Games, and an associate editor of the IEEE Trans. on Computational Intelligence and Games.

Mark J. Nelson is a senior research fellow at the MetaMakers Institute of Falmouth University, an institute dedicated to computational creativity and generative interactive entertainment. He was previously an Assistant Professor at the Center for Computer Games Research, IT University of Copenhagen. He works on AI-based design support for videogames (and other creative design domains), focusing on formalization of things such as game mechanics to enable automated analysis and generation. A long-time vision is an interactive, semiautomated CAD-style system for game prototyping. Prior to the IT University of Copenhagen,he was affiliated with the Expressive Intelligence Studio at the University of California, Santa Cruz, and the School of Interactive Computing at Georgia Institute of Technology.