EAGER: Toward Automatic Generation of Challenge-Driven Interactive Narratives

EAGER：自动生成挑战驱动的互动叙事

• 批准号: 1258305
• 负责人: Michael Mateas
• 金额: $ 15.1万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-12-01 至 2014-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1258305&HistoricalAwards=false
• 关键词: EAGER; Toward; Automatic; Generation; Challenge

This project will conduct the first exploration of a computational system that co-generates intertwined narrative and gameplay progressions. The system will utilize a novel representation called ludo-narrative units (LNUs), representing combinations of narrative, gameplay challenges, and choices. Utilizing audience experience models taking into account phenomena such as player agency, narrative comprehension, and gameplay learning objectives, the system will reason about progressions of narrative choices, narrative exposition, and gameplay challenges, and can dynamically reshape content to match designated goals and audience context. To accomplish this, the project will build an artificial intelligence director to construct interactive scenarios for audiences during their engagement with a game-based narrative.The dynamic construction of scenarios from a pool of authored LNUs would already comprise more flexibility than currently appears in state-of-the-art scenario driven games and other popular interactive narratives, since LNUs can be selected in multiple orders in response to audience activity. But the envisioned system will provide further flexibility and customization through modification of LNU content using story generation technology. Specifically, it will use a story-planning system based on imaginative recall to dynamically provide this content. Further, global narrative and gameplay structure will be provided by using a constraint-solving algorithm to create full experiences satisfying the various system goals, written using answer set programming techniques. This enables the crucial flexibility that allows the system to reason over an arbitrary number of domains without locking it into pre-planned interfaces and infrastructure.A high-level impact of this research will be contributing to a deeper understanding of these scenarios, as it defines them with the level of rigor required for generation. At a more technical level, the research will produce the first system that generates mixed interactive narrative and gameplay guided by shared experience goals. One of the high-level motivations for pursuing this work is that it has potentially profound impact for education, allowing next-generation educational software to benefit from the motivating power of scenarios and to be generated specifically for the learning profile, goals, and progress of particular learners. It is also potentially the case that experiences generated in this manner, and based on these models, could more effectively reach audiences that have grown up with games as a primary media form.

这个项目将进行第一次探索的计算系统，共同产生交织的叙事和游戏进展。该系统将利用一种名为ludo-narrative units（LNUs）的新颖表示法，代表叙事、游戏挑战和选择的组合。利用考虑到玩家代理、叙事理解和游戏玩法学习目标等现象的观众体验模型，系统将推理叙事选择、叙事阐述和游戏玩法挑战的进展，并可以动态重塑内容以匹配指定目标和观众背景。为了实现这一目标，该项目将构建一个人工智能导演，在观众参与基于游戏的叙事期间为他们构建交互式场景。从一组创作的LNU中动态构建场景已经比目前在最先进的场景驱动游戏和其他流行的交互式叙事中表现出更大的灵活性，因为可以响应于观众活动以多个顺序选择LNU。但设想的系统将提供进一步的灵活性和定制通过修改LNU内容使用故事生成技术。具体来说，它将使用一个基于想象回忆的故事规划系统来动态地提供这些内容。此外，全球叙事和游戏结构将通过使用约束求解算法来提供，以创建满足各种系统目标的完整体验，使用答案集编程技术编写。这使得至关重要的灵活性，允许系统的原因，在任意数量的域，而不锁定它到预先计划的接口和基础设施。高层次的影响，这项研究将有助于更深入地了解这些情况下，因为它定义了他们所需的严格程度的生成。在更技术的层面上，这项研究将产生第一个系统，该系统可以生成由共享体验目标指导的混合互动叙事和游戏玩法。追求这项工作的高级动机之一是它对教育有潜在的深远影响，允许下一代教育软件受益于场景的激励力量，并专门针对特定学习者的学习概况，目标和进度生成。以这种方式产生的体验，以及基于这些模型的体验，也可能更有效地接触到那些以游戏为主要媒体形式成长起来的观众。