---
title: "A SAT-based Method for Counting All Singleton Attractors in Boolean Networks"
authors:
  - "Rei Higuchi"
  - "Takehide Soh"
  - "Daniel Le Berre"
  - "Morgan Magnin"
  - "Mutsunori Banbara"
  - "Naoyuki Tamura"
doi: "10.24963/ijcai.2025/290"
url: "https://ijcai.org/proceedings/2025/290"
pdf: "https://ijcai.org/proceedings/2025/0290.pdf"
venue: "Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"
year: 2025
pages: "2601-2609"
track: "Main Track"
keywords:
  - "Constraint Satisfaction and Optimization: CSO: Modeling"
  - "Constraint Satisfaction and Optimization: CSO: Satisfiabilty"
  - "Constraint Satisfaction and Optimization: CSO: Applications"
  - "Constraint Satisfaction and Optimization: CSO: Solvers and tools"
---

# A SAT-based Method for Counting All Singleton Attractors in Boolean Networks

Rei Higuchi, Takehide Soh, Daniel Le Berre, Morgan Magnin, Mutsunori Banbara, Naoyuki Tamura

*Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence*, pages 2601-2609. DOI: [10.24963/ijcai.2025/290](https://doi.org/10.24963/ijcai.2025/290)

## Abstract

Boolean networks (BNs) are widely used to model biological regulatory networks. Attractors here hold significant meaning as they represent long-term behaviors such as homeostasis and the results of cell differentiation. As such, computing attractors is of critical importance to guarantee the validity of a model or to assess its stability and robustness. However, this problem is quite challenging when it comes to large real-world models. To overcome the limits of state-of-the-art BDD-based or ASP-based enumeration approaches, we introduce a SAT-based approach to compute fixed points (singleton attractors) of BN and exhibit its merits for counting the number of singleton attractors of large-scale benchmarks well established in the literature.