SAT-Based Techniques for Lexicographically Smallest Finite Models

Authors

  • Mikoláš Janota Czech Technical University in Prague, Czechia
  • Choiwah Chow Czech Technical University in Prague, Czechia
  • João Araújo Center for Mathematics and Applications (NOVA Math), Portugal Department of Mathematics, NOVA FCT, Portugal
  • Michael Codish Ben-Gurion University of the Negev, Beer-Sheva, Israel
  • Petr Vojtěchovský University of Denver, USA

DOI:

https://doi.org/10.1609/aaai.v38i8.28643

Keywords:

CSO: Satisfiability, CSO: Constraint Satisfaction, CSO: Search, SO: Heuristic Search

Abstract

This paper proposes SAT-based techniques to calculate a specific normal form of a given finite mathematical structure (model). The normal form is obtained by permuting the domain elements so that the representation of the structure is lexicographically smallest possible. Such a normal form is of interest to mathematicians as it enables easy cataloging of algebraic structures. In particular, two structures are isomorphic precisely when their normal forms are the same. This form is also natural to inspect as mathematicians have been using it routinely for many decades. We develop a novel approach where a SAT solver is used in a black-box fashion to compute the smallest representative. The approach constructs the representative gradually and searches the space of possible isomorphisms, requiring a small number of variables. However, the approach may lead to a large number of SAT calls and therefore we devise propagation techniques to reduce this number. The paper focuses on finite structures with a single binary operation (encompassing groups, semigroups, etc.). However, the approach is generalizable to arbitrary finite structures. We provide an implementation of the proposed algorithm and evaluate it on a variety of algebraic structures.

Published

2024-03-24

How to Cite

Janota, M., Chow, C., Araújo, J., Codish, M., & Vojtěchovský, P. (2024). SAT-Based Techniques for Lexicographically Smallest Finite Models. Proceedings of the AAAI Conference on Artificial Intelligence, 38(8), 8048-8056. https://doi.org/10.1609/aaai.v38i8.28643

Issue

Section

AAAI Technical Track on Constraint Satisfaction and Optimization