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        Automatic generation of level maps with the do what's possible representation

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        1905.09618.pdf (PDF, 219Kb)
        Author
        Ashlock, Daniel
        Salge, Christoph
        Attention
        2299/22446
        Abstract
        Automatic generation of level maps is a popular form of automatic content generation. In this study, a recently developed technique employing the do what's possible representation is used to create open-ended level maps. Generation of the map can continue indefinitely, yielding a highly scalable representation. A parameter study is performed to find good parameters for the evolutionary algorithm used to locate high quality map generators. Variations on the technique are presented, demonstrating its versatility, and an algorithmic variant is given that both improves performance and changes the character of maps located. The ability of the map to adapt to different regions where the map is permitted to occupy space are also tested.
        Publication date
        2019-09-26
        Published in
        IEEE Conference on Games 2019, CoG 2019
        Published version
        https://doi.org/10.1109/CIG.2019.8848032
        Other links
        http://hdl.handle.net/2299/22446
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