蕴涵作为因果关系增量生成的逻辑基础

Jingde Cheng, K. Ushijima
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引用次数: 1

摘要

研究了知识工程中的一个问题,以确定如何从已知的因果关系(例如以IF-THEN形式给出的因果关系)中自动生成新的有效因果关系。作者从逻辑的角度讨论了这一问题,并提出利用蕴涵作为因果关系增量生成的原始逻辑基础。在简要比较了关联逻辑与蕴涵逻辑的基础上,定义了蕴涵逻辑的一个子类,给出了它的代数模型,并在此基础上证明了它的合理性,并在此基础上讨论了演绎蕴涵推理。因此,对于给定的因果关系,可以通过基于逻辑的演绎蕴涵推理生成新的有效因果关系
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entailment as a logical basis for incremental generation of causal relations
A problem in knowledge engineering is investigated in order to determine how to generate automatically new valid causal relations from some known causal relations (e.g. given with the IF-THEN form). The authors discuss this problem from a logical viewpoint and propose using the entailment that is a primitive logical basis for the incremental generation of causal relations. After a brief comparison between relevance logics and entailment logic, the authors define a subclass of entailment logic, given an algebraic model for it, show its soundness based on the model, and discuss deductive entailment reasoning based on the logic. As a result, for given causal relations, new valid causal relations can be generated by deductive entailment reasoning based on the logic.<>
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