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Linear Logic for Non-Linear Storytelling

机译:非线性讲故事的线性逻辑

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Whilst narrative representations have played a prominent role in AI research, there has been a renewed interest in the topic with the development of interactive narratives. A typical approach aims at generating narratives from baseline action representations, most often using planning techniques. However, this research has developed empirically, often as an application of planning. In this paper, we explore a more rigorous formalisation of narrative concepts, both at the action level and at the plot level. Our aim is to investigate how to bridge the gap between action descriptions and narrative concepts, by considering the latter from the perspective of resource consumption and causality. We propose to use Linear Logic, often introduced as a logic of resources, for it provides, through linear implication, a better description of causality than in Classical and Intuitionistic Logic. Besides advances in the fundamental principles of narrative formalisation, this approach can support the formal validation of scenario description as a preliminary step to their implementation via other computational formalisms.
机译:虽然叙事表征在AI研究中发挥着突出的作用,但在开发互动叙事的主题上有一种新的兴趣。典型的方法旨在从基线动作表示产生叙述,最常使用规划技术。然而,这项研究经常开发,往往是规划的应用。在本文中,我们探讨了叙事概念的更严格形式化,无论是在行动水平和情节级别。我们的目标是通过考虑资源消费和因果关系的角度,调查如何弥合行动描述和叙事概念之间的差距。我们建议使用线性逻辑,经常被引入资源逻辑,因为它通过线性暗示提供了比古典和直觉逻辑的应变描述。除了叙事形式化的基本原则的进步外,这种方法可以通过其他计算形​​式主义支持将场景描述的正式验证作为其实施的初步步骤。

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