Abstract

The logical means of detecting empirical regularities using the JSM method of automated research support are considered. Generators of hypotheses about the causes and hypotheses about predictions that are stored in sequences of expandable fact bases are determined. Many “histories of possible worlds” are considered, where “world” refers to an expandable fact base. This set is used to determine empirical regularities, that is, empirical laws, tendencies, and weak tendencies. Empirical regularities are used to determine empirical modalities of necessity (for empirical laws), possibilities (for empirical tendencies), and weak possibilities (for weak empirical tendencies). The Propositional calculi of the class ERA are proposed, that is, modal logics with two empirical modalities of necessity and possibility such that they imitate abductive inference through the axioms of abduction (◻(p → q) & Tq) → ◻p), (◇(p → q) & Tq) → ◇p), where ◻, ◇, T are operators of necessity, possibility, and truth (“it is true that…”). A series of definitions related to the characterization of data mining using heuristics of the JSM method of automated research support is given.

中文翻译：

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关于JSM研究的启发式方法（文章的补充）

摘要

考虑了使用自动研究支持的JSM方法检测经验规律性的逻辑方法。确定关于原因的假设的生成者和关于可扩展事实基础的序列中存储的预测的假设。考虑了许多“可能世界的历史”，其中“世界”是指可扩展的事实基础。该集合用于确定经验规律性，即经验定律，趋势和弱趋势。经验规律性用于确定必要性（对于经验定律），可能性（对于经验趋势）和弱可能性（对于弱经验趋势）的经验模式。提出了ERA类的命题演算，即p → q）Tq的）→◻ p），（◇（p → q）Tq的）→◇ p），其中◻，◇，牛逼的必要性，可能性和真理的运营商（“这是真的......” ）。给出了一系列与使用自动研究支持的JSM方法的启发式方法进行数据挖掘表征有关的定义。