DFU.Vol6.12191.61.pdf
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Procedural Content Generation: Goals, Challenges and Actionable Steps
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Artificial and Computational Intelligence in Games (DFU - Vol. 6)
Series: Dagstuhl Follow-Ups (DFU) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2013-11-18
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Julian Togelius, Alex J. Champandard, Pier Luca Lanzi, Michael Mateas, Ana Paiva, Mike Preuss, and Kenneth O. Stanley. Procedural Content Generation: Goals, Challenges and Actionable Steps. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 61-75, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)
https://doi.org/10.4230/DFU.Vol6.12191.61
https://doi.org/10.4230/DFU.Vol6.12191.61
Abstract
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.
Keywords
- procedural content generation
- video games
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