- Series: Computational Synthesis and Creative Systems
- Hardcover: 237 pages
- Publisher: Springer; 1st ed. 2016 edition (October 19, 2016)
- Language: English
- ISBN-10: 3319427148
- ISBN-13: 978-3319427140
- Product Dimensions: 6.1 x 0.6 x 9.2 inches
- Shipping Weight: 1 pounds (View shipping rates and policies)
- Average Customer Review: 3 customer reviews
- Amazon Best Sellers Rank: #1,244,729 in Books (See Top 100 in Books)
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Procedural Content Generation in Games (Computational Synthesis and Creative Systems) 1st ed. 2016 Edition
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From the Back Cover
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.
About the Author
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.
Top customer reviews
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Another complaint is that the images, graphs and other visual aids in the book are often too small to be useful. What should be a full page diagram will often be less than a 3rd of a page rendering any text within it unreadable and any symbols to small to distinguish.
While I did find the book somewhat interesting, it ultimately felt like a waste of time since it did little to advance my understanding of PCG.
The book is described as being good for both game developers and students. The lack of useful detail makes it useless for either. Consistently, throughout the book, the authors will pick a problem space and then mention some algorithms and or techniques which have been used to address the problems. This is fine but they never give enough information to understand the algorithms much less enough for the reader to implement them. And when discussing multiple approaches to a problem they rarely mention the trade-offs between the choices. Inevitably the paragraph ends with a reference to a paper and the text moves on.
The bulk of the coverage in the book is for the procedural generation of game levels for 2d games. This is no surprise given that this seems to be the focus of most of the authors’ published papers. Other areas of procedural content generation are either slighted or ignored altogether. Music is mentioned in passing. Procedural animation is ignored altogether. Why no mention of using Perlin Noise to animate characters or the wonderful procedural animation done in Spore? Terrain is at least hand-waved over but if you really care you should get “Texturing & Modeling, A Procedural Approach” by Ebert et al. I promise, you’ll learn much more.
I’m not really quite sure what to say about the equating of noise and terrain. Noise is not content but it can be used to generate content. The whole section feels like it was done by someone who isn’t well versed with the topic.
Ultimately the references are the only real value in the book. Even here, the value is lessened since the references are listed per-chapter and no master list is given. As a bonus the book also fails to have an appendix.