Narrative Planning: Balancing Plot and Character
Narrative Planning: Balancing Plot and Character
复制标题
DOI：
10.1613/jair.2989
复制
发表时间：
2010-01-01
影响因子：
5
通讯作者：
Young, R. Michael
中科院分区：
文献类型：
--
作者：
Riedl, Mark O.;Young, R. Michael
叙述，尤其是讲故事，是人类体验的重要组成部分。因此，能够对叙事进行推理的计算系统可以成为更有效的沟通者、表演者、教育者和培训师。计算叙事推理的核心挑战之一是叙事生成，即自动创建有意义的事件序列。有许多因素——逻辑和美学——促成了叙事人工制品的成功。这种成功的核心是它的理解能力。我们认为叙事的以下两个属性是普遍的：(a)情节的逻辑因果进展，以及(b)人物的可信度。角色可信度是指观众认为角色的行为不会对观众的怀疑产生负面影响。具体来说，角色必须被观众视为有意的代理人。在这篇文章中，我们探索了将精炼搜索作为解决叙事生成问题的一种技术的使用——找到一个可靠的、可信的角色序列，将初始世界状态转换为目标命题所持有的世界状态。我们描述了一种新颖的优化搜索规划算法——基于意图的偏序因果联系（IPOCL）规划器——除了创建因果合理的情节进展之外，还通过识别可能的角色目标来解释他们的行为，并创建计划结构来解释为什么这些角色致力于他们的目标。我们提出了一项实证评估结果，表明由IPOCL算法生成的叙事计划比传统的部分顺序计划生成的计划更能支持观众对角色意图的理解。
Narrative, and in particular story telling, is an important part of the human experience. Consequently, computational systems that can reason about narrative can be more effective communicators, entertainers, educators, and trainers. One of the central challenges in computational narrative reasoning is narrative generation, the automated creation of meaningful event sequences. There are many factors - logical and aesthetic - that contribute to the success of a narrative artifact. Central to this success is its understand ability. We argue that the following two attributes of narratives are universal: (a) thelogical causal progression of plot, and (b) character believability. Character believability is the perception by the audience that the actions performed by characters do not negatively impact the audience's suspension of disbelief. Specifically, characters must be perceived by the audience to be intentional agents. In this article, we explore the use of refinement search as a technique for solving the narrative generation problem - to find a sound and believable sequence of characteractions that transforms an initial world state into a world state in which goal propositions hold. We describe a novel refinement search planning algorithm - the Intent-based Partial Order Causal Link (IPOCL) planner - that, in addition to creating causally sound plot progression, reasons about character intentionality by identifying possible character goals that explain their actions and creating plan structures that explain why those characters commit to their goals. We present the results of an empirical evaluation that demonstrates that narrative plans generated by the IPOCL algorithm support audience comprehension of character intentions better than plans generated by conventional partial-order planners.