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Record Nr. |
UNINA9910255013303321 |
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Autore |
Shaker Noor |
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Titolo |
Procedural Content Generation in Games / / by Noor Shaker, Julian Togelius, Mark J. Nelson |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XVI, 237 p. 103 illus., 57 illus. in color.) |
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Collana |
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Computational Synthesis and Creative Systems, , 2509-6575 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computer games—Programming |
Computational intelligence |
User interfaces (Computer systems) |
Application software |
Artificial Intelligence |
Game Development |
Computational Intelligence |
User Interfaces and Human Computer Interaction |
Computer Appl. in Arts and Humanities |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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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Sommario/riassunto |
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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 |
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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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