3 research outputs found

    Characteristics of generatable games

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    We address the problem of generating complete games, rather than content for existing games. In particular, we try to an- swer the question which types of games it would be realistic or even feasible to generate. To begin to answer the question, we rst list the di erent ways we see that games could be generated, and then try to discuss what characterises games that would be comparatively easy or hard to generate. The discussion is structured according to a subset of the charac- teristics discussed in the book Characteristics of Games by Elias, Gar eld and Gutschera.peer-reviewe

    Data adventures

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    This paper outlines a system for generating adventure games based on open data, and describes a sketch of the system implementation at its current state. The adventure game genre has been popular for a long time and differs signi cantly in design priorities from game genres which are commonly addressed in PCG research. In order to create believable and engaging content, we use data from DBpedia to generate the game's non-playable characters locations and plot, and OpenStreetMaps to create the game's levels.peer-reviewe

    A constructive approach for the generation of underwater environments

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    This paper introduces Coralize, a library of generators for marine organisms such as corals and sponges. Using constructive algorithms, Coralize can generate stony corals via L-system grammars, soft corals via leaf venation algorithms and sponges via nutrient-based mesh growth. The generative algorithms are parameterizable, allowing a user to adjust the parameters in order to create visually appealing 3D meshes. Such meshes can be used to automatically populate a seabed or reef, in order to create a biologically realistic and aesthetically pleasing underwater environment.The research was supported, in part, by the FP7 ICT projects C2Learn (project no: 318480) and ILearnRW (project no: 318803), and by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).peer-reviewe
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