License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DFU.Vol6.12191.61
URN: urn:nbn:de:0030-drops-43367
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Togelius, Julian ; Champandard, Alex J. ; Lanzi, Pier Luca ; Mateas, Michael ; Paiva, Ana ; Preuss, Mike ; Stanley, Kenneth O.

Procedural Content Generation: Goals, Challenges and Actionable Steps

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This chapter discusses the challenges and opportunities of procedural content generation (PCG) in games. It starts with defining three grand goals of PCG, namely multi-level multicontent PCG, PCG-based game design and generating complete games. The way these goals are defined, they are not feasible with current technology. Therefore we identify nine challenges for PCG research. Work towards meeting these challenges is likely to take us closer to realising the three grand goals. In order to help researchers get started, we also identify five actionable steps, which PCG researchers could get started working on immediately.

BibTeX - Entry

  author =	{Julian Togelius and Alex J. Champandard and Pier Luca Lanzi and Michael Mateas and Ana Paiva and Mike Preuss and Kenneth O. Stanley},
  title =	{{Procedural Content Generation: Goals, Challenges and Actionable Steps}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{61--75},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Simon M. Lucas and Michael Mateas and Mike Preuss and Pieter Spronck and Julian Togelius},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-43367},
  doi =		{10.4230/DFU.Vol6.12191.61},
  annote =	{Keywords: procedural content generation, video games}

Keywords: procedural content generation, video games
Collection: Artificial and Computational Intelligence in Games
Issue Date: 2013
Date of publication: 18.11.2013

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