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TCIAIG
2010

Modeling Player Experience for Content Creation

9 years 5 months ago
Modeling Player Experience for Content Creation
In this paper, we use computational intelligence techniques to built quantitative models of player experience for a platform game. The models accurately predict certain key affective states of the player based on both gameplay metrics that relate to the actions performed by the player in the game, and on parameters of the level that was played. For the experiments presented here, a version of the classic Super Mario Bros game is enhanced with parameterizable level generation and gameplay metrics collection. Player pairwise preference data is collected using forced choice questionnaires, and the models are trained using this data and neuro-evolutionary preference learning of multi-layer perceptrons. The derived models will be used to optimize design parameters for particular types of player experience, allowing the designer to automatically generate unique levels that induce the desired experience for the player.
Christopher Pedersen, Julian Togelius, Georgios N.
Added 21 May 2011
Updated 21 May 2011
Type Journal
Year 2010
Where TCIAIG
Authors Christopher Pedersen, Julian Togelius, Georgios N. Yannakakis
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