This paper presents a generative system for the automatic creation of video game levels. Our approach is novel in that it allows high-level design goals to be expressed in a top-down manner, while existing bottom-up techniques do not. We use the FI-2Pop genetic algorithm as a natural way to express both constraints and optimization goals for potential level designs. We develop a genetic encoding technique specific to level design, which proves to be extremely flexible. Example levels are generated for two different genres of game, demonstrating the system's broad applicability. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Sorenson, N., & Pasquier, P. (2010). Towards a generic framework for automated video game level creation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6024 LNCS, pp. 131–140). Springer Verlag. https://doi.org/10.1007/978-3-642-12239-2_14
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