Deduction is the one of the major forms of inferences and commonly used in formal logic. This kind of inference has the feature of monotonicity, which can be problematic. There are different types of inferences that are not monotonic, e.g. abductive inferences. The debate between advocates and critics of abduction as a useful instrument can be reconstructed along the issue, how an abductive inference warrants to pick out one hypothesis as the best one. But how can the goodness of an inference be assessed? Material inferences express good inferences based on the principle of material incompatibility. Material inferences are based on modal vocabulary, which enriches the logical expressivity of the inferential relations. This leads also to certain limits in the application of labeling in machine learning. I propose a modal interpretation of implications to express conceptual relations.

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推理和模态词汇

演绎是推理的主要形式之一，常用于形式逻辑。这种推理具有单调性的特点，可能会出现问题。有不同类型的推理不是单调的，例如溯因推理。可以围绕以下问题重新构建绑架作为一种有用工具的支持者和批评者之间的辩论，即绑架推理如何保证挑选出一个假设为最佳假设。但是如何评估推理的优劣呢？材料推论基于材料不相容的原则表达良好的推论。物质推理以情态词汇为基础，丰富了推理关系的逻辑表达能力。这也导致标记在机器学习中的应用受到一定限制。