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CB-POCL: A Choice-Based Algorithm for Character Personality in Planning-based Narrative Generation

机译:CB-pOCL:基于规划的叙事生成中基于选择的人格人格算法

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摘要

The quality and believability of a story can be significantly enhanced by the presence of compelling characters. Characters can be made more compelling by the portrayal of a distinguishable personality. This paper presents an algorithm that formalizes an approach previously described for the incorporation of character personality in narrative that is automatically generated. The approach is based on a computational model that operationalizes personality as behavior that results from the choices made by characters in the course of a story. This operationalization is based on the Big Five personality structure and results from behavioral psychology studies that link behavior to personality traits.
机译:引人入胜的角色的存在可以大大提高故事的质量和可信度。通过鲜明的个性刻画可以使人物更引人注目。本文提出了一种算法,该算法形式化了先前描述的将角色个性纳入自动生成的叙事中的方法。该方法基于一个计算模型,该模型将个性化为行为,该行为是由故事过程中角色做出的选择导致的。这种可操作性基于“五大”人格结构,是将行为与人格特质联系起来的行为心理学研究的结果。

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