Rule-based reasoning is an essential part of human intelligence prominently formalized in artificial intelligence research via logic programs. Describing complex objects as the composition of elementary ones is a common strategy in computer science and science in general. The author has recently introduced the sequential composition of logic programs in the context of logic-based analogical reasoning and learning in logic programming. Motivated by these applications, in this paper we construct a qualitative and algebraic notion of syntactic logic program similarity from sequential decompositions of programs. We then show how similarity can be used to answer queries across different domains via a one-step reduction. In a broader sense, this paper is a further step towards an algebra of logic programs first envisioned by Richard O. Keefe in 1985 with applications to analogical reasoning.

翻译：基于规则的推理是人类通过逻辑程序进行人工智能研究中明显正式确定的基本人类情报的一部分。 将复杂物体作为基本物体的构成称为计算机科学和一般科学的共同战略。 作者最近在逻辑模拟推理和逻辑编程中学习的背景下引入了逻辑程序顺序的构成。 受这些应用的驱动,我们在本文件中构建了一个质量和代数概念,即共性逻辑程序与程序相近的相近性。 然后,我们展示了如何通过一步骤的缩减使用相似性来回答不同领域的询问。 从更广泛的意义上讲,本文是朝着最初由Richard O. Keefe于1985年设想的逻辑方案的代数,以及模拟推理的应用迈出的又一步。