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Answer Set Programming for Declarative Content Specification: A Scalable Partitioning-Based Approach

机译:声明性内容规范的答案集编程:一种基于可扩展分区的方法

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Procedural Content Generation is applied in the development process of many commercial games: automatically generated game contents are delivered to players in order to offer a constantly changing user experience and enrich the game itself. Usually, the generative process relies on search-based non-deterministic algorithms, which encode one or more techniques for guaranteeing "legal" yet diversified output. Declarative approaches to content generation, more properly defined as Declarative Content Specification techniques, like the ones based on Answer Set Programming, allow to focus on describing content requirements rather than programming ad-hoc generation engines, and to fast prototype generation techniques themselves. This work investigates to what extent ASP-based DCS is scalable enough for industrial contexts, by proposing a partitioning-based approach. A working prototype, available as an Unity Asset and as a GVGAI framework level generator is presented.
机译:程序内容生成被应用在许多商业游戏的开发过程中:自动生成的游戏内容被交付给玩家,以提供不断变化的用户体验并丰富游戏本身。通常,生成过程依赖于基于搜索的非确定性算法,该算法对一种或多种技术进行编码以保证“合法”却多样化的输出。内容生成的声明性方法(更恰当地定义为声明性内容规范技术)(例如基于“答案集编程”的方法)允许专注于描述内容需求,而不是对即席生成引擎进行编程,并专注于快速原型生成技术本身。这项工作通过提出一种基于分区的方法,调查了基于ASP的DCS在工业环境中可扩展到什么程度。展示了一个可用的原型,可以作为Unity资产和GVGAI框架级别生成器使用。

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