# On syntactically similar logic programs and sequential decompositions

arXiv: https://arxiv.org/abs/2109.05300 · HTML: https://mlsanity.com/paper/2109.05300/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 17 references that are in the map.
- First posted on arXiv 11 Sep 2021.

## Builds on (most cited first, 2 of 2)

- [Logic program proportions](https://mlsanity.com/paper/1809.09938/) (2018)
- [Sequential composition of answer set programs](https://mlsanity.com/paper/2104.12156/) (2021)

## Built on by (most cited first, 1 of 1)

- [Sequential decomposition of propositional logic programs](https://mlsanity.com/paper/2304.13522/) (2023)

## Abstract (arXiv)

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 algebraic theory of logic programming.