Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/22970
Title: Towards automatic personalized content generation for platform games
Authors: Shaker, Noor
Yannakakis, Georgios N.
Togelius, Julian
Keywords: Computer games -- Design and construction
Level design (Computer science)
Issue Date: 2010
Publisher: ACM Publications
Citation: Shaker, N., Yannakakis, G. N., & Togelius, J. (2010). Towards automatic personalized content generation for platform games. Sixth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, Stanford. 63-68.
Abstract: In this paper, we show that personalized levels can be automatically generated for platform games. We build on previous work, where models were derived that predicted player experience based on features of level design and on playing styles. These models are constructed using preference learning, based on questionnaires administered to players after playing different levels. The contributions of the current paper are (1) more accurate models based on a much larger data set; (2) a mechanism for adapting level design parameters to given players and playing style; (3) evaluation of this adaptation mechanism using both algorithmic and human players. The results indicate that the adaptation mechanism effectively optimizes level design parameters for particular players.
URI: https://www.um.edu.mt/library/oar//handle/123456789/22970
Appears in Collections:Scholarly Works - InsDG

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