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• W2023532087 abstract "This paper presents a search-based method for generating maps for the popular real-time strategy (RTS) game StarCraft. We devise a representation of StarCraft maps suitable for evolutionary search, along with a set of fitness functions based on predicted entertainment value of those maps, as derived from theories of player experience. A multiobjective evolutionary algorithm is then used to evolve complete StarCraft maps based on the representation and selected fitness functions. The output of this algorithm is a Pareto front approximation visualizing the tradeoff between the several fitness functions used, and where each point on the front represents a viable map. We argue that this method is useful for both automatic and machine-assisted map generation, and in particular that the Pareto fronts are excellent design support tools for human map designers." @default.
• W2023532087 created "2016-06-24" @default.
• W2023532087 creator A5010479168 @default.
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• W2023532087 date "2010-08-01" @default.
• W2023532087 modified "2023-10-14" @default.
• W2023532087 title "Multiobjective exploration of the StarCraft map space" @default.
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• W2023532087 doi "https://doi.org/10.1109/itw.2010.5593346" @default.
• W2023532087 hasPublicationYear "2010" @default.
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