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| Artikel-Nr.: 5667A-9783031167218 Herst.-Nr.: 9783031167218 EAN/GTIN: 9783031167218 |
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 | 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. Weitere Informationen:  |  | Author: | Matthew Guzdial; Sam Snodgrass; Adam J. Summerville | Verlag: | Springer International Publishing | Sprache: | eng |
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 | Weitere Suchbegriffe: allgemeine Informatikbücher - englischsprachig, allgemeine informatikbücher - englischsprachig, Artificial Intelligence; Computational Creativity; Computer Science; Game Design; Machine Learning; PCGML; Procedural content generation; video games, Procedural Content Generation, Machine Learning, Artificial Intelligence, Video Games, Game Design, Computational Creativity, Computer Science, PCGML |
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