Semantic Content Generation Framework for Game Worlds

    Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review


    As virtual worlds in games become larger and more
    detailed, the need for rich, interactive content to realistically
    populate these worlds becomes greater. Content is expensive
    and slow to create manually and does not scale once created.
    Procedural content generation offers an attractive alternative for
    providing this content. There are several methods for generating
    different types of content including terrain and some types of
    organisms. However, these methods are hard to control and
    can give inconsistent results. A method of providing a high
    level, semantic context to such procedural methods may offer a
    potential solution. Such an approach may also allow manually
    created content to be placed appropriately and in a scalable
    manner in the world. Finally, semantic knowledge may be used
    to annotate content to allow greater interactivity and improved
    AI. This paper suggests such a method. Making use of semantic
    networks for storing knowledge about the potential content of
    the virtual world and using stateful graph traversal algorithms
    to convert the semantic knowledge into concrete instances, this
    method supports the procedural generation of rich complex
    content for virtual worlds.
    Original languageEnglish
    Title of host publication2014 6th International Conference on Games and Virtual Worlds for Serious Applications
    Publication statusPublished - 2014


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