Search-Based Procedural Content Generation

  • Julian Togelius
  • Georgios N. Yannakakis
  • Kenneth O. Stanley
  • Cameron Browne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)


Recently, a small number of papers have appeared in which the authors implement stochastic search algorithms, such as evolutionary computation, to generate game content, such as levels, rules and weapons. We propose a taxonomy of such approaches, centring on what sort of content is generated, how the content is represented, and how the quality of the content is evaluated. The relation between search-based and other types of procedural content generation is described, as are some of the main research challenges in this new field. The paper ends with some successful examples of this approach.


Game Design Board Game Player Experience Game Rule Game Mechanic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Julian Togelius
    • 1
  • Georgios N. Yannakakis
    • 1
  • Kenneth O. Stanley
    • 2
  • Cameron Browne
    • 3
  1. 1.IT University of CopenhagenCopenhagenDenmark
  2. 2.University of Central FloridaOrlando
  3. 3.Imperial College LondonLondonUK

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