Generating Game Levels of Diverse Behaviour Engagement
21-24 Aug. 2022
Recent years, there has been growing interests in experience-driven procedural level generation. Various metrics have been formulated to model player experience and help generate personalised levels. In this work, we question whether experience metrics can adapt to agents with different personas. We start by reviewing existing metrics for evaluating game levels. Then, focusing on platformer games, we design a framework integrating various agents and evaluation metrics. Experimental studies on Super Mario Bros. indicate that using the same evaluation metrics but agents with different personas can generate levels for particular persona. It implies that, for simple games, using a game-playing agent of specific player archetype as a level tester is probably all we need to generate levels of diverse behaviour engagement.
First ; Corresponding
National Natural Science Foundation of China;Shenzhen Fundamental Research Program[JCYJ20190809121403553];
Cited Times [WOS]:0
|Document Type||Conference paper|
|Department||Southern University of Science and Technology|
1.Research Institute of Trustworthy Autonomous System,Southern University of Science and Technology (SUSTech),Shenzhen,China
2.Southern University of Science and Technology (SUSTech),Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Department of Computer Science and Engineering,Shenzhen,China
|First Author Affilication||Southern University of Science and Technology; Department of Computer Science and Engineering|
|Corresponding Author Affilication||Southern University of Science and Technology; Department of Computer Science and Engineering|
|First Author's First Affilication||Southern University of Science and Technology|
Zhang，Keyuan,Bai，Jiayu,Liu，Jialin. Generating Game Levels of Diverse Behaviour Engagement[C],2022:167-174.
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