Syllogistic reasoning, that is the drawing of inferences for categorical‐quantified assertions, is one of the oldest branches of deductive reasoning research with a history exceeding 100 years. In syllogistic reasoning experiments, “No Valid Conclusion” (NVC) is one of the most frequently selected responses and corresponds to the logically correct conclusion for 58% of the syllogistic problem domain. To date, NVC is often neglected in computational models or just treated as a by‐product of the underlying inferential mechanisms such as a last resort when the search for alternatives is exhausted. We illustrate that NVC represents a major shortcoming of current models for human syllogistic reasoning. By introducing heuristic rules for predicting NVC, we demonstrate that simple extensions of the existing models result in substantial improvements in their predictive performances. Our results emphasize the need for better NVC handling in cognitive modeling of human reasoning and provide directions for modelers on how to enhance their approaches.

中文翻译：

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模拟人类三段论推理：“没有有效结论”的作用。

三段论推理，即对分类量化的断言进行推理的方法，是演绎推理研究最古老的分支之一，已有超过100年的历史。在三段论推理实验中，“无有效结论”（NVC）是最常选择的响应之一，对应于58％的三段论问题域的逻辑正确结论。迄今为止，NVC通常在计算模型中被忽略，或者仅被视为潜在推论机制的副产品，例如在穷举无穷的情况下不得已而为之。我们说明，NVC代表了人类三段论推理的当前模型的主要缺陷。通过引入启发式规则来预测NVC，我们证明了对现有模型的简单扩展会大大改善其预测性能。我们的结果强调在人类推理的认知建模中需要更好地处理NVC，并为建模人员提供有关如何增强其方法的指导。