Many of the stories we are exposed to are built from small schemas of connected events involving a set of characters–boy meets girl leads to a relationship or crime leads to revenge. The present paper proposes an evolutionary solution to the task of putting together a story by combining a set of such schemas. This approach presents three challenges: how to mix up the elements in the different schemas, how to instantiate the characters across the schemas and how to tell acceptable combinations from the rest. The present paper applies an evolutionary solution that relies on a genetic representation for these combinations of schemas, and applies as fitness functions a set of metrics on compatibility constraints across schema combinations. Outputs of this procedure are evaluated by human judges in comparison with baseline solutions in which the values for genes are assigned at random. The proposed solution generates a population of story drafts that resemble plot descriptions for simple stories. The results of the comparative evaluation by human judges are positive. The genetic representation of pattern combinations and the metrics on compatibility across pattern pairs provide a valid evolutionary solution for constructing simple plots.

我们接触到的许多故事都是由涉及一组角色的相关事件的小模式构建的——男孩遇见女孩导致一段关系或犯罪导致报复. 本文提出了一种进化解决方案，通过组合一组这样的模式来组合故事。这种方法提出了三个挑战：如何混合不同模式中的元素，如何跨模式实例化字符，以及如何从其余的中分辨出可接受的组合。本文应用了一种进化解决方案，该解决方案依赖于这些模式组合的遗传表示，并将一组关于跨模式组合的兼容性约束的指标作为适应度函数应用。该程序的输出由人类法官与基线解决方案进行评估，在基线解决方案中，基因值是随机分配的。提议的解决方案会生成大量故事草稿，类似于简单故事的情节描述。人类法官的比较评估结果是积极的。模式组合的遗传表示和模式对间兼容性的度量为构建简单地块提供了有效的进化解决方案。