AAAI Publications, Sixth Artificial Intelligence and Interactive Digital Entertainment Conference

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Towards Automatic Personalized Content Generation for Platform Games
Noor Shaker, Georgios Yannakakis, Julian Togelius

Last modified: 2010-10-10


In this paper, we show that personalized levels can be auto- matically generated for platform games. We build on previ- ous 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 learn- ing, based on questionnaires administered to players after playing different levels. The contributions of the current pa- per 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 adap- tation mechanism using both algorithmic and human players. The results indicate that the adaptation mechanism effectively optimizes level design parameters for particular players.


Game Adaptation; Player Modeling

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