DendryScope:通过符号分析支持叙事设计师

Jasmine Otto, Autumn Chen, Adam M. Smith
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引用次数: 0

摘要

基于质量的叙事(QBN)是具有广泛隐含链接结构的超文本。对一篇文章的观察可能对其他文章的可达性产生不明显的长期影响,这对作者提出了挑战。为了帮助叙事设计师解决这个问题,我们制作了一个界面,从视觉上总结了所有可能的游戏轨迹。我们的界面利用答案集编程在可能的游戏轨迹上生成查询语言,允许叙事设计师深入挖掘有趣的场景。我们通过DendryScope工具介绍这个接口,该工具接受大多数用Dendry语言编写的qbn。我们通过采访四位叙事设计师来评估DendryScope,因为他们使用该工具来探索Bee (Emily Short撰写的著名QBN)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DendryScope: Narrative Designer Support via Symbolic Analysis
Quality-based narratives (QBN) are hypertexts with extensive implicit linked structure. The observation of one passage can have non-obvious long-range implications for the reachability of other passages, which poses an authoring challenge. To help narrative designers address this issue, we produced an interface which visually summarizes all possible playtraces. Our interface leverages answer set programming to produce a query language over possible playtraces, allowing narrative designers to drill down to interesting scenarios. We introduce this interface through the DendryScope tool, which accepts most QBNs written in the Dendry language. We evaluated DendryScope by interviewing four narrative designers as they used the tool to explore Bee, a notable QBN written by Emily Short.
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