Cube-based Isomorph-free Finite Model Finding

Fuente: arXiv
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Hauptverfasser: Chow, Choiwah, Janota, Mikoláš, Araújo, João
Format: Preprint
Veröffentlicht: 2025
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author Chow, Choiwah
Janota, Mikoláš
Araújo, João
author_facet Chow, Choiwah
Janota, Mikoláš
Araújo, João
contents Complete enumeration of finite models of first-order logic (FOL) formulas is pivotal to universal algebra, which studies and catalogs algebraic structures. Efficient finite model enumeration is highly challenging because the number of models grows rapidly with their size but at the same time, we are only interested in models modulo isomorphism. While isomorphism cuts down the number of models of interest, it is nontrivial to take that into account computationally. This paper develops a novel algorithm that achieves isomorphism-free enumeration by employing isomorphic graph detection algorithm nauty, cube-based search space splitting, and compact model representations. We name our algorithm cube-based isomorph-free finite model finding algorithm (CBIF). Our approach contrasts with the traditional two-step algorithms, which first enumerate (possibly isomorphic) models and then filter the isomorphic ones out in the second stage. The experimental results show that CBIF is many orders of magnitude faster than the traditional two-step algorithms. CBIF enables us to calculate new results that are not found in the literature, including the extension of two existing OEIS sequences, thereby advancing the state of the art.
format Preprint
id arxiv_https___arxiv_org_abs_2501_08157
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cube-based Isomorph-free Finite Model Finding
Chow, Choiwah
Janota, Mikoláš
Araújo, João
Logic in Computer Science
Complete enumeration of finite models of first-order logic (FOL) formulas is pivotal to universal algebra, which studies and catalogs algebraic structures. Efficient finite model enumeration is highly challenging because the number of models grows rapidly with their size but at the same time, we are only interested in models modulo isomorphism. While isomorphism cuts down the number of models of interest, it is nontrivial to take that into account computationally. This paper develops a novel algorithm that achieves isomorphism-free enumeration by employing isomorphic graph detection algorithm nauty, cube-based search space splitting, and compact model representations. We name our algorithm cube-based isomorph-free finite model finding algorithm (CBIF). Our approach contrasts with the traditional two-step algorithms, which first enumerate (possibly isomorphic) models and then filter the isomorphic ones out in the second stage. The experimental results show that CBIF is many orders of magnitude faster than the traditional two-step algorithms. CBIF enables us to calculate new results that are not found in the literature, including the extension of two existing OEIS sequences, thereby advancing the state of the art.
title Cube-based Isomorph-free Finite Model Finding
topic Logic in Computer Science
url https://arxiv.org/abs/2501.08157