This paper naturalizes inductive inference by showing how scientific knowledge of real mechanisms provides large benefits to it. I show how knowledge about mechanisms contributes to generalization, inference to the best explanation, causal inference, and reasoning with probabilities. Generalization from some A are B to all A are B is more plausible when a mechanism connects A to B. Inference to the best explanation is strengthened when the explanations are mechanistic and when explanatory hypotheses are themselves mechanistically explained. Causal inference in medical explanation, counterfactual reasoning, and analogy also benefit from mechanistic connections. Mechanisms also help with problems concerning the interpretation, availability, and computation of probabilities.

中文翻译：

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自然化逻辑：机制知识如何增强归纳推理

本文通过展示真实机制的科学知识如何为其带来巨大好处，使归纳推理自然化。我展示了有关机制的知识如何有助于泛化、最佳解释推理、因果推理和概率推理。当机制将 A 与 B 联系起来时，从一些 A 是 B 到所有 A 是 B 的概括更合理。当解释是机械的并且解释假设本身被​​机械解释时，对最佳解释的推断会得到加强。医学解释、反事实推理和类比中的因果推断也受益于机械联系。机制还有助于解决有关概率的解释、可用性和计算的问题。