基于角色的计算故事叙述模型

Leonid Berov
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引用次数: 4

摘要

我的论文旨在概念化和实现一个叙事生成的计算模型,该模型由叙事学理论和认知多智能体模拟模型提供信息。它通过对虚构角色采取模仿立场来解决这个问题,并研究如何从基于多智能体系统的深度角色模型中计算再现与角色相关的叙事现象。基于这样的叙事概念,本文探讨了如何控制情节的产生,以及如何在虚构人物的依赖下评估最终情节的质量。通过实施评价性叙事系统,它有助于研究计算创造力,并通过提出基于几个后结构主义描述理论的生成叙事理论,为叙事学做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Character Focused Narrative Models for Computational Storytelling
My thesis aims at conceptualizing and implementing a computational model of narrative generation that is informed by narratological theory as well as cognitive multi-agent simulation models. It approaches this problem by taking a mimetic stance towards fictional characters and investigates how narrative phenomena related to characters can be computationally recreated from a deep character model grounded in multi agent systems. Based on such a conceptualization of narrative it explores how the generation of plot can be controlled, and how the quality of the resulting plot can be evaluated, in dependence of fictional characters. By that it contributes to research on computational creativity by implementing an evaluative storytelling system, and to narratology by proposing a generative narrative theory based on several post-structuralist descriptive theories.
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